{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Knowledge-based-Recommender-System.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "IhY_79CI31QH"
      ],
      "authorship_tag": "ABX9TyP39AGjke3UKtl3Djg2eY1v",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/rposhala/Recommender-System-on-MovieLens-dataset/blob/main/Knowledge_based_Recommender_System.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I6QppVIb871O"
      },
      "source": [
        "import os\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "#from scipy.sparse import csr_matrix\n",
        "#from sklearn.neighbors import NearestNeighbors\n",
        "#from sklearn.model_selection import train_test_split"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e2b-97_pD3_X"
      },
      "source": [
        "## Loading MovieLens rating dataset of size 100k"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QBxz0KI-D3Xa"
      },
      "source": [
        "DATASET_LINK='http://files.grouplens.org/datasets/movielens/ml-100k.zip'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OIUrxfX2EXKP"
      },
      "source": [
        "## if done in jupyter notebook on a local machine\n",
        "\n",
        "# !conda install -c anaconda wget --yes"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IhxnKWueEfCT",
        "outputId": "308fba5a-fcb5-4cf0-c529-8eb8c3677730",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 629
        }
      },
      "source": [
        "!wget -nc http://files.grouplens.org/datasets/movielens/ml-100k.zip\n",
        "!unzip -n ml-100k.zip"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2020-10-16 01:11:02--  http://files.grouplens.org/datasets/movielens/ml-100k.zip\n",
            "Resolving files.grouplens.org (files.grouplens.org)... 128.101.65.152\n",
            "Connecting to files.grouplens.org (files.grouplens.org)|128.101.65.152|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 4924029 (4.7M) [application/zip]\n",
            "Saving to: ‘ml-100k.zip’\n",
            "\n",
            "ml-100k.zip         100%[===================>]   4.70M  16.3MB/s    in 0.3s    \n",
            "\n",
            "2020-10-16 01:11:02 (16.3 MB/s) - ‘ml-100k.zip’ saved [4924029/4924029]\n",
            "\n",
            "Archive:  ml-100k.zip\n",
            "   creating: ml-100k/\n",
            "  inflating: ml-100k/allbut.pl       \n",
            "  inflating: ml-100k/mku.sh          \n",
            "  inflating: ml-100k/README          \n",
            "  inflating: ml-100k/u.data          \n",
            "  inflating: ml-100k/u.genre         \n",
            "  inflating: ml-100k/u.info          \n",
            "  inflating: ml-100k/u.item          \n",
            "  inflating: ml-100k/u.occupation    \n",
            "  inflating: ml-100k/u.user          \n",
            "  inflating: ml-100k/u1.base         \n",
            "  inflating: ml-100k/u1.test         \n",
            "  inflating: ml-100k/u2.base         \n",
            "  inflating: ml-100k/u2.test         \n",
            "  inflating: ml-100k/u3.base         \n",
            "  inflating: ml-100k/u3.test         \n",
            "  inflating: ml-100k/u4.base         \n",
            "  inflating: ml-100k/u4.test         \n",
            "  inflating: ml-100k/u5.base         \n",
            "  inflating: ml-100k/u5.test         \n",
            "  inflating: ml-100k/ua.base         \n",
            "  inflating: ml-100k/ua.test         \n",
            "  inflating: ml-100k/ub.base         \n",
            "  inflating: ml-100k/ub.test         \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vpA1EWM-KVoT"
      },
      "source": [
        "## u.info     -- The number of users, items, and ratings in the u data set."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GHDq1-JlEooc",
        "outputId": "b2004e87-18e6-4224-b4cf-e53895608ba3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "overall_stats = pd.read_csv('ml-100k/u.info', header=None)\n",
        "print(\"Details of users, items and ratings involved in the loaded movielens dataset: \",list(overall_stats[0]))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Details of users, items and ratings involved in the loaded movielens dataset:  ['943 users', '1682 items', '100000 ratings']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6kRw5oLJIofy"
      },
      "source": [
        "## u.data     -- The full u data set, 100000 ratings by 943 users on 1682 items.\n",
        "\n",
        "              Each user has rated at least 20 movies.  Users and items are\n",
        "              numbered consecutively from 1.  The data is randomly ordered. This is a tab separated list of \n",
        "\t         user id | item id | rating | timestamp. \n",
        "              The time stamps are unix seconds since 1/1/1970 UTC "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bWag-M0KHbKk",
        "outputId": "b1a73b61-7662-4e5c-ecd1-ec9063d5a4ed",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "## same item id is same as movie id, item id column is renamed as movie id\n",
        "column_names1 = ['user id','movie id','rating','timestamp']\n",
        "dataset = pd.read_csv('ml-100k/u.data', sep='\\t',header=None,names=column_names1)\n",
        "dataset.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>user id</th>\n",
              "      <th>movie id</th>\n",
              "      <th>rating</th>\n",
              "      <th>timestamp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>196</td>\n",
              "      <td>242</td>\n",
              "      <td>3</td>\n",
              "      <td>881250949</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>186</td>\n",
              "      <td>302</td>\n",
              "      <td>3</td>\n",
              "      <td>891717742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>22</td>\n",
              "      <td>377</td>\n",
              "      <td>1</td>\n",
              "      <td>878887116</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>244</td>\n",
              "      <td>51</td>\n",
              "      <td>2</td>\n",
              "      <td>880606923</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>166</td>\n",
              "      <td>346</td>\n",
              "      <td>1</td>\n",
              "      <td>886397596</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   user id  movie id  rating  timestamp\n",
              "0      196       242       3  881250949\n",
              "1      186       302       3  891717742\n",
              "2       22       377       1  878887116\n",
              "3      244        51       2  880606923\n",
              "4      166       346       1  886397596"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uWiCCCZfQrBJ",
        "outputId": "af7bcc44-3684-41ac-86ab-ba0f864ded05",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "len(dataset), max(dataset['movie id']),min(dataset['movie id'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(100000, 1682, 1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2bVpYrebKvzh"
      },
      "source": [
        "## u.item     -- Information about the items (movies); this is a tab separated\n",
        "              list of\n",
        "              movie id | movie title | release date | video release date |\n",
        "              IMDb URL | unknown | Action | Adventure | Animation |\n",
        "              Children's | Comedy | Crime | Documentary | Drama | Fantasy |\n",
        "              Film-Noir | Horror | Musical | Mystery | Romance | Sci-Fi |\n",
        "              Thriller | War | Western |\n",
        "              The last 19 fields are the genres, a 1 indicates the movie\n",
        "              is of that genre, a 0 indicates it is not; movies can be in\n",
        "              several genres at once.\n",
        "              The movie ids are the ones used in the u.data data set.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "40FkKuG6M9tS",
        "outputId": "3d17019f-b479-4dec-fcab-c8387572a376",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        }
      },
      "source": [
        "d = 'movie id | movie title | release date | video release date | IMDb URL | unknown | Action | Adventure | Animation | Children | Comedy | Crime | Documentary | Drama | Fantasy | Film-Noir | Horror | Musical | Mystery | Romance | Sci-Fi | Thriller | War | Western'\n",
        "column_names2 = d.split(' | ')\n",
        "column_names2"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['movie id',\n",
              " 'movie title',\n",
              " 'release date',\n",
              " 'video release date',\n",
              " 'IMDb URL',\n",
              " 'unknown',\n",
              " 'Action',\n",
              " 'Adventure',\n",
              " 'Animation',\n",
              " 'Children',\n",
              " 'Comedy',\n",
              " 'Crime',\n",
              " 'Documentary',\n",
              " 'Drama',\n",
              " 'Fantasy',\n",
              " 'Film-Noir',\n",
              " 'Horror',\n",
              " 'Musical',\n",
              " 'Mystery',\n",
              " 'Romance',\n",
              " 'Sci-Fi',\n",
              " 'Thriller',\n",
              " 'War',\n",
              " 'Western']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rOFkTodrJQIi",
        "outputId": "c31ed623-7d48-4022-9465-6038fb3f164d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 779
        }
      },
      "source": [
        "items_dataset = pd.read_csv('ml-100k/u.item', sep='|',header=None,names=column_names2,encoding='latin-1')\n",
        "items_dataset"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie id</th>\n",
              "      <th>movie title</th>\n",
              "      <th>release date</th>\n",
              "      <th>video release date</th>\n",
              "      <th>IMDb URL</th>\n",
              "      <th>unknown</th>\n",
              "      <th>Action</th>\n",
              "      <th>Adventure</th>\n",
              "      <th>Animation</th>\n",
              "      <th>Children</th>\n",
              "      <th>Comedy</th>\n",
              "      <th>Crime</th>\n",
              "      <th>Documentary</th>\n",
              "      <th>Drama</th>\n",
              "      <th>Fantasy</th>\n",
              "      <th>Film-Noir</th>\n",
              "      <th>Horror</th>\n",
              "      <th>Musical</th>\n",
              "      <th>Mystery</th>\n",
              "      <th>Romance</th>\n",
              "      <th>Sci-Fi</th>\n",
              "      <th>Thriller</th>\n",
              "      <th>War</th>\n",
              "      <th>Western</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Toy Story (1995)</td>\n",
              "      <td>01-Jan-1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Toy%20Story%2...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>GoldenEye (1995)</td>\n",
              "      <td>01-Jan-1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?GoldenEye%20(...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Four Rooms (1995)</td>\n",
              "      <td>01-Jan-1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Four%20Rooms%...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Get Shorty (1995)</td>\n",
              "      <td>01-Jan-1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Get%20Shorty%...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Copycat (1995)</td>\n",
              "      <td>01-Jan-1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Copycat%20(1995)</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1677</th>\n",
              "      <td>1678</td>\n",
              "      <td>Mat' i syn (1997)</td>\n",
              "      <td>06-Feb-1998</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Mat%27+i+syn+...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1678</th>\n",
              "      <td>1679</td>\n",
              "      <td>B. Monkey (1998)</td>\n",
              "      <td>06-Feb-1998</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?B%2E+Monkey+(...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1679</th>\n",
              "      <td>1680</td>\n",
              "      <td>Sliding Doors (1998)</td>\n",
              "      <td>01-Jan-1998</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/Title?Sliding+Doors+(1998)</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1680</th>\n",
              "      <td>1681</td>\n",
              "      <td>You So Crazy (1994)</td>\n",
              "      <td>01-Jan-1994</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?You%20So%20Cr...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1681</th>\n",
              "      <td>1682</td>\n",
              "      <td>Scream of Stone (Schrei aus Stein) (1991)</td>\n",
              "      <td>08-Mar-1996</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Schrei%20aus%...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1682 rows × 24 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      movie id                                movie title  ... War  Western\n",
              "0            1                           Toy Story (1995)  ...   0        0\n",
              "1            2                           GoldenEye (1995)  ...   0        0\n",
              "2            3                          Four Rooms (1995)  ...   0        0\n",
              "3            4                          Get Shorty (1995)  ...   0        0\n",
              "4            5                             Copycat (1995)  ...   0        0\n",
              "...        ...                                        ...  ...  ..      ...\n",
              "1677      1678                          Mat' i syn (1997)  ...   0        0\n",
              "1678      1679                           B. Monkey (1998)  ...   0        0\n",
              "1679      1680                       Sliding Doors (1998)  ...   0        0\n",
              "1680      1681                        You So Crazy (1994)  ...   0        0\n",
              "1681      1682  Scream of Stone (Schrei aus Stein) (1991)  ...   0        0\n",
              "\n",
              "[1682 rows x 24 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7tB4z-ZGNp3O",
        "outputId": "8e83ce0b-737d-48b5-e4d6-0dccd77d3ab8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "movie_dataset = items_dataset[['movie id','movie title']]\n",
        "movie_dataset.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie id</th>\n",
              "      <th>movie title</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Toy Story (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>GoldenEye (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Four Rooms (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Get Shorty (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Copycat (1995)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   movie id        movie title\n",
              "0         1   Toy Story (1995)\n",
              "1         2   GoldenEye (1995)\n",
              "2         3  Four Rooms (1995)\n",
              "3         4  Get Shorty (1995)\n",
              "4         5     Copycat (1995)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uKus60hs-axf"
      },
      "source": [
        "## Merging required datasets"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "l3jlxk2aVW9l",
        "outputId": "64a68706-89ed-4bfc-d08a-b0ddf744a811",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "merged_dataset = pd.merge(dataset, movie_dataset, how='inner', on='movie id')\n",
        "merged_dataset.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>user id</th>\n",
              "      <th>movie id</th>\n",
              "      <th>rating</th>\n",
              "      <th>timestamp</th>\n",
              "      <th>movie title</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>196</td>\n",
              "      <td>242</td>\n",
              "      <td>3</td>\n",
              "      <td>881250949</td>\n",
              "      <td>Kolya (1996)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>63</td>\n",
              "      <td>242</td>\n",
              "      <td>3</td>\n",
              "      <td>875747190</td>\n",
              "      <td>Kolya (1996)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>226</td>\n",
              "      <td>242</td>\n",
              "      <td>5</td>\n",
              "      <td>883888671</td>\n",
              "      <td>Kolya (1996)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>154</td>\n",
              "      <td>242</td>\n",
              "      <td>3</td>\n",
              "      <td>879138235</td>\n",
              "      <td>Kolya (1996)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>306</td>\n",
              "      <td>242</td>\n",
              "      <td>5</td>\n",
              "      <td>876503793</td>\n",
              "      <td>Kolya (1996)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   user id  movie id  rating  timestamp   movie title\n",
              "0      196       242       3  881250949  Kolya (1996)\n",
              "1       63       242       3  875747190  Kolya (1996)\n",
              "2      226       242       5  883888671  Kolya (1996)\n",
              "3      154       242       3  879138235  Kolya (1996)\n",
              "4      306       242       5  876503793  Kolya (1996)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UJAxMMi1bmNi",
        "outputId": "eb33d1fa-2316-4930-cec0-0a53e1c4717f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        }
      },
      "source": [
        "merged_dataset.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>user id</th>\n",
              "      <th>movie id</th>\n",
              "      <th>rating</th>\n",
              "      <th>timestamp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>100000.00000</td>\n",
              "      <td>100000.000000</td>\n",
              "      <td>100000.000000</td>\n",
              "      <td>1.000000e+05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>462.48475</td>\n",
              "      <td>425.530130</td>\n",
              "      <td>3.529860</td>\n",
              "      <td>8.835289e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>266.61442</td>\n",
              "      <td>330.798356</td>\n",
              "      <td>1.125674</td>\n",
              "      <td>5.343856e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.00000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>8.747247e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>254.00000</td>\n",
              "      <td>175.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>8.794487e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>447.00000</td>\n",
              "      <td>322.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>8.828269e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>682.00000</td>\n",
              "      <td>631.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>8.882600e+08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>943.00000</td>\n",
              "      <td>1682.000000</td>\n",
              "      <td>5.000000</td>\n",
              "      <td>8.932866e+08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            user id       movie id         rating     timestamp\n",
              "count  100000.00000  100000.000000  100000.000000  1.000000e+05\n",
              "mean      462.48475     425.530130       3.529860  8.835289e+08\n",
              "std       266.61442     330.798356       1.125674  5.343856e+06\n",
              "min         1.00000       1.000000       1.000000  8.747247e+08\n",
              "25%       254.00000     175.000000       3.000000  8.794487e+08\n",
              "50%       447.00000     322.000000       4.000000  8.828269e+08\n",
              "75%       682.00000     631.000000       4.000000  8.882600e+08\n",
              "max       943.00000    1682.000000       5.000000  8.932866e+08"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8qYU51YO-fhs"
      },
      "source": [
        "## Data Visualization & Recommendations through Data Analysis for a new user (Content-based & Popularity based Recommender system)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q_tjBrrjdgOR",
        "outputId": "acedeec5-43c8-46ac-c2af-64a625676d2f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 404
        }
      },
      "source": [
        "merged_dataset['rating'].value_counts(sort=False).plot(kind='bar' ,figsize=(10,6), use_index = True, rot=0)\n",
        "plt.title('Bar plot of rating frequency')\n",
        "plt.xlabel('Rating')\n",
        "plt.ylabel('Number of times a rating was given')\n",
        "label = list(merged_dataset['rating'].value_counts(sort=False))\n",
        "r4 = [1,2,3,4,5]\n",
        "for i in range(len(label)):\n",
        "  plt.text(x = r4[i]-1.2 , y = label[i]+500, s = label[i], size =15)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ddCUhcSekW3A"
      },
      "source": [
        "We can observe that most of the users have rewarded movies they watched with a 4 star rating and followed by 3 star and 5 star."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8JVGzz1rd_Ex"
      },
      "source": [
        "avg_highly_rated_movies = merged_dataset.groupby(['movie title']).agg({\"rating\":\"mean\"})['rating'].sort_values(ascending=False)\n",
        "avg_highly_rated_movies = avg_highly_rated_movies.to_frame()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QajiCkKfq5Bi",
        "outputId": "3f5c2a6d-4655-458f-8ad9-e2e0c5306cda",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 700
        }
      },
      "source": [
        "avg_highly_rated_movies.head(20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>movie title</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Marlene Dietrich: Shadow and Light (1996)</th>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Prefontaine (1997)</th>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Santa with Muscles (1996)</th>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Star Kid (1997)</th>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Someone Else's America (1995)</th>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Entertaining Angels: The Dorothy Day Story (1996)</th>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Saint of Fort Washington, The (1993)</th>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Great Day in Harlem, A (1994)</th>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>They Made Me a Criminal (1939)</th>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Aiqing wansui (1994)</th>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pather Panchali (1955)</th>\n",
              "      <td>4.625000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Anna (1996)</th>\n",
              "      <td>4.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Everest (1998)</th>\n",
              "      <td>4.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Maya Lin: A Strong Clear Vision (1994)</th>\n",
              "      <td>4.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Some Mother's Son (1996)</th>\n",
              "      <td>4.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Close Shave, A (1995)</th>\n",
              "      <td>4.491071</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Schindler's List (1993)</th>\n",
              "      <td>4.466443</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Wrong Trousers, The (1993)</th>\n",
              "      <td>4.466102</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Casablanca (1942)</th>\n",
              "      <td>4.456790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Wallace &amp; Gromit: The Best of Aardman Animation (1996)</th>\n",
              "      <td>4.447761</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                      rating\n",
              "movie title                                                 \n",
              "Marlene Dietrich: Shadow and Light (1996)           5.000000\n",
              "Prefontaine (1997)                                  5.000000\n",
              "Santa with Muscles (1996)                           5.000000\n",
              "Star Kid (1997)                                     5.000000\n",
              "Someone Else's America (1995)                       5.000000\n",
              "Entertaining Angels: The Dorothy Day Story (1996)   5.000000\n",
              "Saint of Fort Washington, The (1993)                5.000000\n",
              "Great Day in Harlem, A (1994)                       5.000000\n",
              "They Made Me a Criminal (1939)                      5.000000\n",
              "Aiqing wansui (1994)                                5.000000\n",
              "Pather Panchali (1955)                              4.625000\n",
              "Anna (1996)                                         4.500000\n",
              "Everest (1998)                                      4.500000\n",
              "Maya Lin: A Strong Clear Vision (1994)              4.500000\n",
              "Some Mother's Son (1996)                            4.500000\n",
              "Close Shave, A (1995)                               4.491071\n",
              "Schindler's List (1993)                             4.466443\n",
              "Wrong Trousers, The (1993)                          4.466102\n",
              "Casablanca (1942)                                   4.456790\n",
              "Wallace & Gromit: The Best of Aardman Animation...  4.447761"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I5U5xzYnsA9e",
        "outputId": "fd0474ba-4489-468c-e71d-8d875e3533ea",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "print(\"Number of movies with 5 star rating on average: \",len(avg_highly_rated_movies[avg_highly_rated_movies['rating'] == 5.0]))\n",
        "print(\"Number of movies with above 4 star and below 5 star rating on average: \",len(avg_highly_rated_movies[(avg_highly_rated_movies['rating'] >= 4.0) & (avg_highly_rated_movies['rating'] < 5.0)]))\n",
        "print(\"Number of movies with above 3 star and below 4 star rating on average: \",len(avg_highly_rated_movies[(avg_highly_rated_movies['rating'] >= 3.0) & (avg_highly_rated_movies['rating'] < 4.0)]))\n",
        "print(\"Number of movies with above 2 star and below 3 star rating on average: \",len(avg_highly_rated_movies[(avg_highly_rated_movies['rating'] >= 2.0) & (avg_highly_rated_movies['rating'] < 3.0)]))\n",
        "print(\"Number of movies with above 1 star and below 2 star rating on average: \",len(avg_highly_rated_movies[(avg_highly_rated_movies['rating'] >= 1.0) & (avg_highly_rated_movies['rating'] < 2.0)]))\n",
        "print(\"Number of movies with below 1 star rating on average: \", len(avg_highly_rated_movies[(avg_highly_rated_movies['rating'] < 1.0)]))\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Number of movies with 5 star rating on average:  10\n",
            "Number of movies with above 4 star and below 5 star rating on average:  163\n",
            "Number of movies with above 3 star and below 4 star rating on average:  871\n",
            "Number of movies with above 2 star and below 3 star rating on average:  492\n",
            "Number of movies with above 1 star and below 2 star rating on average:  128\n",
            "Number of movies with below 1 star rating on average:  0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wqDuh9tOwQN1"
      },
      "source": [
        "We can look at number of movies between each range of average ratings:  \n",
        "if  \n",
        "rating ==5.0 : 10;  \n",
        "4<= rating <5: 163;  \n",
        "3<= rating <4: 871;    \n",
        "2<= rating <3: 492;  \n",
        "1<= rating <2: 128;\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7VNSqthl_2kU",
        "outputId": "ec045f0d-207a-49c2-b98c-ef3ba08754de",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 270
        }
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "print('Split of movies count based on their overall average rating')\n",
        "# Pie chart, where the slices will be ordered and plotted counter-clockwise:\n",
        "labels = '5 star', '4 to 5 star', '3 to 4 star', '2 to 3 star', '1 to 2 star'\n",
        "sizes = [10, 163, 871, 492, 128]\n",
        "# explode = (0, 0.1, 0, 0)  # only \"explode\" the 2nd slice (i.e. 'Hogs')\n",
        "\n",
        "fig1, ax1 = plt.subplots()\n",
        "ax1.pie(sizes, labels=labels, autopct='%1.1f%%',\n",
        "        shadow=True, startangle=90)\n",
        "ax1.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
        "\n",
        "plt.show()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Split of movies count based on their overall average rating\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zZOCXhY4zhIC"
      },
      "source": [
        "avg_highly_rated_movies.reset_index(level=0, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5wHFoMWfti41",
        "outputId": "9f9ada96-218c-4811-b20a-dface04ed64b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        }
      },
      "source": [
        "avg_highly_rated_movies.columns = ['movie title', 'avg rating']\n",
        "\n",
        "avg_highly_rated_movies.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie title</th>\n",
              "      <th>avg rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Marlene Dietrich: Shadow and Light (1996)</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Prefontaine (1997)</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Santa with Muscles (1996)</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Star Kid (1997)</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Someone Else's America (1995)</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Entertaining Angels: The Dorothy Day Story (1996)</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Saint of Fort Washington, The (1993)</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Great Day in Harlem, A (1994)</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>They Made Me a Criminal (1939)</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Aiqing wansui (1994)</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                         movie title  avg rating\n",
              "0         Marlene Dietrich: Shadow and Light (1996)          5.0\n",
              "1                                 Prefontaine (1997)         5.0\n",
              "2                          Santa with Muscles (1996)         5.0\n",
              "3                                    Star Kid (1997)         5.0\n",
              "4                      Someone Else's America (1995)         5.0\n",
              "5  Entertaining Angels: The Dorothy Day Story (1996)         5.0\n",
              "6               Saint of Fort Washington, The (1993)         5.0\n",
              "7                      Great Day in Harlem, A (1994)         5.0\n",
              "8                     They Made Me a Criminal (1939)         5.0\n",
              "9                               Aiqing wansui (1994)         5.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dyYfsNRsz5f5"
      },
      "source": [
        "These are the top 10 movies that can be naviely suggested to the new users, **Recommendations based on top average ratings.**\n",
        "\n",
        "-----------------------------"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Peh1-b6uo01E",
        "outputId": "00c3f7f6-cee8-4cd9-dd91-6f0b2c94eb3a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        }
      },
      "source": [
        "merged_dataset.groupby(['movie title']).agg({\"rating\":\"sum\"})['rating'].sort_values(ascending=False)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "movie title\n",
              "Star Wars (1977)                  2541\n",
              "Fargo (1996)                      2111\n",
              "Return of the Jedi (1983)         2032\n",
              "Contact (1997)                    1936\n",
              "Raiders of the Lost Ark (1981)    1786\n",
              "                                  ... \n",
              "Leopard Son, The (1996)              1\n",
              "Liebelei (1933)                      1\n",
              "Bird of Prey (1996)                  1\n",
              "Lotto Land (1995)                    1\n",
              "Daens (1992)                         1\n",
              "Name: rating, Length: 1664, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F7ZJn-uKpdWU",
        "outputId": "e8797c10-4283-4a8a-ec1c-b76a022bbca0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        }
      },
      "source": [
        "merged_dataset['movie id'].value_counts(sort=False).plot(kind='bar' ,figsize=(20,6), use_index = True, rot=0)\n",
        "plt.title('Bar plot of frequency of a movie being watched')\n",
        "plt.xlabel('Movies')\n",
        "plt.ylabel('Number of times a user watched that movie')\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Number of times a user watched that movie')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "moiyNVt4qWmN"
      },
      "source": [
        "We can see that very few movies were watched by more than 100 out of 943 users.\n",
        "\n",
        "--------------------------"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RagHlO7Disd8"
      },
      "source": [
        "popular_movies = merged_dataset.groupby(['movie title']).agg({\"rating\":\"count\"})['rating'].sort_values(ascending=False)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DpJbtChW1nHy"
      },
      "source": [
        "popular_movies = popular_movies.to_frame()\n",
        "popular_movies.reset_index(level=0, inplace=True)\n",
        "popular_movies.columns = ['movie title', 'Number of Users watched']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T-EaOu_v2hDo",
        "outputId": "3adf8cc3-66cd-43a2-b36d-20b991b40aec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "print(\"Number of popular movies with more than 500 viewers: \",len(popular_movies[popular_movies['Number of Users watched'] >= 500]))\n",
        "print(\"Number of popular movies with more than 400 and less than 500 viewers: \",len(popular_movies[(popular_movies['Number of Users watched'] >= 400) & (popular_movies['Number of Users watched'] < 500)]))\n",
        "print(\"Number of popular movies with more than 300 and less than 400 viewers: \",len(popular_movies[(popular_movies['Number of Users watched'] >= 300) & (popular_movies['Number of Users watched'] < 400)]))\n",
        "print(\"Number of popular movies with more than 200 and less than 300 viewers: \",len(popular_movies[(popular_movies['Number of Users watched'] >= 200) & (popular_movies['Number of Users watched'] < 300)]))\n",
        "print(\"Number of popular movies with more than 100 and less than 200 viewers: \",len(popular_movies[(popular_movies['Number of Users watched'] >= 100) & (popular_movies['Number of Users watched'] < 200)]))\n",
        "print(\"Number of popular movies with less than 100 viewers: \", len(popular_movies[(popular_movies['Number of Users watched'] < 100)]))\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Number of popular movies with more than 500 viewers:  4\n",
            "Number of popular movies with more than 400 and less than 500 viewers:  8\n",
            "Number of popular movies with more than 300 and less than 400 viewers:  22\n",
            "Number of popular movies with more than 200 and less than 300 viewers:  84\n",
            "Number of popular movies with more than 100 and less than 200 viewers:  220\n",
            "Number of popular movies with less than 100 viewers:  1326\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "650SkeJKBspi",
        "outputId": "fb433772-b7c8-48c4-93e1-9c12f18e6654",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 303
        }
      },
      "source": [
        "\n",
        "df = pd.DataFrame({'viewers': [4, 8, 22, 84, 220, 1326]},\n",
        "                  index=['500 viewers', '400 to 500 viewers', '300 to 400 viewers', '200 to 300 viewers', '100 to 200 viewers', 'less than 100 viewers'])\n",
        "plot = df.plot.pie(y='viewers', figsize=(5, 5))\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b71P43rd3sBA"
      },
      "source": [
        "We can consider the movies which have more than 400 viewers as **POPULAR** and there are 12 movies.\n",
        "\n",
        "-------------------------"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0Fehdsj82DF4",
        "outputId": "1aa6001c-c53c-477d-fabc-4dd2332d7d1d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        }
      },
      "source": [
        "popular_movies[popular_movies['Number of Users watched'] >= 400]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie title</th>\n",
              "      <th>Number of Users watched</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Star Wars (1977)</td>\n",
              "      <td>583</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Contact (1997)</td>\n",
              "      <td>509</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Fargo (1996)</td>\n",
              "      <td>508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Return of the Jedi (1983)</td>\n",
              "      <td>507</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Liar Liar (1997)</td>\n",
              "      <td>485</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>English Patient, The (1996)</td>\n",
              "      <td>481</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Scream (1996)</td>\n",
              "      <td>478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Toy Story (1995)</td>\n",
              "      <td>452</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Air Force One (1997)</td>\n",
              "      <td>431</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Independence Day (ID4) (1996)</td>\n",
              "      <td>429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Raiders of the Lost Ark (1981)</td>\n",
              "      <td>420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Godfather, The (1972)</td>\n",
              "      <td>413</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                       movie title  Number of Users watched\n",
              "0                 Star Wars (1977)                      583\n",
              "1                   Contact (1997)                      509\n",
              "2                     Fargo (1996)                      508\n",
              "3        Return of the Jedi (1983)                      507\n",
              "4                 Liar Liar (1997)                      485\n",
              "5      English Patient, The (1996)                      481\n",
              "6                    Scream (1996)                      478\n",
              "7                 Toy Story (1995)                      452\n",
              "8             Air Force One (1997)                      431\n",
              "9    Independence Day (ID4) (1996)                      429\n",
              "10  Raiders of the Lost Ark (1981)                      420\n",
              "11           Godfather, The (1972)                      413"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pQcVlaTn4PQj"
      },
      "source": [
        "These are the most popular movies which can be recommended to a new user. **Recommendations based on Popularity**\n",
        "\n",
        "----------------------------"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aHp-8l0i2GRx",
        "outputId": "24638608-421b-457d-bc3c-031b1f874c4b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        }
      },
      "source": [
        "highly_rated_popular_movies = pd.merge(avg_highly_rated_movies, popular_movies, how = 'inner', on='movie title')\n",
        "highly_rated_popular_movies.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie title</th>\n",
              "      <th>avg rating</th>\n",
              "      <th>Number of Users watched</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Marlene Dietrich: Shadow and Light (1996)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Prefontaine (1997)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Santa with Muscles (1996)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Star Kid (1997)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Someone Else's America (1995)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Entertaining Angels: The Dorothy Day Story (1996)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Saint of Fort Washington, The (1993)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Great Day in Harlem, A (1994)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>They Made Me a Criminal (1939)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Aiqing wansui (1994)</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                         movie title  ...  Number of Users watched\n",
              "0         Marlene Dietrich: Shadow and Light (1996)   ...                        1\n",
              "1                                 Prefontaine (1997)  ...                        3\n",
              "2                          Santa with Muscles (1996)  ...                        2\n",
              "3                                    Star Kid (1997)  ...                        3\n",
              "4                      Someone Else's America (1995)  ...                        1\n",
              "5  Entertaining Angels: The Dorothy Day Story (1996)  ...                        1\n",
              "6               Saint of Fort Washington, The (1993)  ...                        2\n",
              "7                      Great Day in Harlem, A (1994)  ...                        1\n",
              "8                     They Made Me a Criminal (1939)  ...                        1\n",
              "9                               Aiqing wansui (1994)  ...                        1\n",
              "\n",
              "[10 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F0PXjIWA7Vt1",
        "outputId": "95e8b529-79c8-4bc6-fd59-534f1601ccbb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        }
      },
      "source": [
        "highly_rated_popular_movies[highly_rated_popular_movies['Number of Users watched']>400]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie title</th>\n",
              "      <th>avg rating</th>\n",
              "      <th>Number of Users watched</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Star Wars (1977)</td>\n",
              "      <td>4.358491</td>\n",
              "      <td>583</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>Godfather, The (1972)</td>\n",
              "      <td>4.283293</td>\n",
              "      <td>413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>Raiders of the Lost Ark (1981)</td>\n",
              "      <td>4.252381</td>\n",
              "      <td>420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>64</th>\n",
              "      <td>Fargo (1996)</td>\n",
              "      <td>4.155512</td>\n",
              "      <td>508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>129</th>\n",
              "      <td>Return of the Jedi (1983)</td>\n",
              "      <td>4.007890</td>\n",
              "      <td>507</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>236</th>\n",
              "      <td>Toy Story (1995)</td>\n",
              "      <td>3.878319</td>\n",
              "      <td>452</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>292</th>\n",
              "      <td>Contact (1997)</td>\n",
              "      <td>3.803536</td>\n",
              "      <td>509</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>412</th>\n",
              "      <td>English Patient, The (1996)</td>\n",
              "      <td>3.656965</td>\n",
              "      <td>481</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>428</th>\n",
              "      <td>Air Force One (1997)</td>\n",
              "      <td>3.631090</td>\n",
              "      <td>431</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>597</th>\n",
              "      <td>Scream (1996)</td>\n",
              "      <td>3.441423</td>\n",
              "      <td>478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>598</th>\n",
              "      <td>Independence Day (ID4) (1996)</td>\n",
              "      <td>3.438228</td>\n",
              "      <td>429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>837</th>\n",
              "      <td>Liar Liar (1997)</td>\n",
              "      <td>3.156701</td>\n",
              "      <td>485</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        movie title  avg rating  Number of Users watched\n",
              "23                 Star Wars (1977)    4.358491                      583\n",
              "34            Godfather, The (1972)    4.283293                      413\n",
              "40   Raiders of the Lost Ark (1981)    4.252381                      420\n",
              "64                     Fargo (1996)    4.155512                      508\n",
              "129       Return of the Jedi (1983)    4.007890                      507\n",
              "236                Toy Story (1995)    3.878319                      452\n",
              "292                  Contact (1997)    3.803536                      509\n",
              "412     English Patient, The (1996)    3.656965                      481\n",
              "428            Air Force One (1997)    3.631090                      431\n",
              "597                   Scream (1996)    3.441423                      478\n",
              "598   Independence Day (ID4) (1996)    3.438228                      429\n",
              "837                Liar Liar (1997)    3.156701                      485"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h7dmoDb-567R",
        "outputId": "e190d556-15e9-4580-dae0-d3c1111919b7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        }
      },
      "source": [
        "highly_rated_popular_movies[(highly_rated_popular_movies['Number of Users watched']>300) & (highly_rated_popular_movies['avg rating']>=4.0)]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie title</th>\n",
              "      <th>avg rating</th>\n",
              "      <th>Number of Users watched</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Star Wars (1977)</td>\n",
              "      <td>4.358491</td>\n",
              "      <td>583</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>Silence of the Lambs, The (1991)</td>\n",
              "      <td>4.289744</td>\n",
              "      <td>390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>Godfather, The (1972)</td>\n",
              "      <td>4.283293</td>\n",
              "      <td>413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>Raiders of the Lost Ark (1981)</td>\n",
              "      <td>4.252381</td>\n",
              "      <td>420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>Titanic (1997)</td>\n",
              "      <td>4.245714</td>\n",
              "      <td>350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>Empire Strikes Back, The (1980)</td>\n",
              "      <td>4.204360</td>\n",
              "      <td>367</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>61</th>\n",
              "      <td>Princess Bride, The (1987)</td>\n",
              "      <td>4.172840</td>\n",
              "      <td>324</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>64</th>\n",
              "      <td>Fargo (1996)</td>\n",
              "      <td>4.155512</td>\n",
              "      <td>508</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>Monty Python and the Holy Grail (1974)</td>\n",
              "      <td>4.066456</td>\n",
              "      <td>316</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101</th>\n",
              "      <td>Pulp Fiction (1994)</td>\n",
              "      <td>4.060914</td>\n",
              "      <td>394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>114</th>\n",
              "      <td>Fugitive, The (1993)</td>\n",
              "      <td>4.044643</td>\n",
              "      <td>336</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>129</th>\n",
              "      <td>Return of the Jedi (1983)</td>\n",
              "      <td>4.007890</td>\n",
              "      <td>507</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                movie title  ...  Number of Users watched\n",
              "23                         Star Wars (1977)  ...                      583\n",
              "32         Silence of the Lambs, The (1991)  ...                      390\n",
              "34                    Godfather, The (1972)  ...                      413\n",
              "40           Raiders of the Lost Ark (1981)  ...                      420\n",
              "45                           Titanic (1997)  ...                      350\n",
              "49          Empire Strikes Back, The (1980)  ...                      367\n",
              "61               Princess Bride, The (1987)  ...                      324\n",
              "64                             Fargo (1996)  ...                      508\n",
              "98   Monty Python and the Holy Grail (1974)  ...                      316\n",
              "101                     Pulp Fiction (1994)  ...                      394\n",
              "114                    Fugitive, The (1993)  ...                      336\n",
              "129               Return of the Jedi (1983)  ...                      507\n",
              "\n",
              "[12 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w-cVM7If7dRZ"
      },
      "source": [
        "These movies are the best to suggest to a new user as they are popular and well rated by the users who already watched them. These have rating more than 4 with atleast 300 viewers.\n",
        "\n",
        "**Recommendations based popularity and rating. These are top rated popular movies**\n",
        "\n",
        "----------------------------\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AAvexcTZDUtm"
      },
      "source": [
        "## Recommendations based on Movie Genre to a New User."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c3sMtrPbEhjk",
        "outputId": "25f6b200-0ec2-4e07-a33b-ad9af50ca329",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 340
        }
      },
      "source": [
        "movie_genre_list = column_names2[-19:]\n",
        "movie_genre_list"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['unknown',\n",
              " 'Action',\n",
              " 'Adventure',\n",
              " 'Animation',\n",
              " 'Children',\n",
              " 'Comedy',\n",
              " 'Crime',\n",
              " 'Documentary',\n",
              " 'Drama',\n",
              " 'Fantasy',\n",
              " 'Film-Noir',\n",
              " 'Horror',\n",
              " 'Musical',\n",
              " 'Mystery',\n",
              " 'Romance',\n",
              " 'Sci-Fi',\n",
              " 'Thriller',\n",
              " 'War',\n",
              " 'Western']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AshrvmaNFNwZ",
        "outputId": "95352581-178d-4758-bc74-72a320da6408",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        }
      },
      "source": [
        "count = []\n",
        "for i in movie_genre_list:\n",
        "  # print(i)\n",
        "  genre_based_movies = items_dataset[['movie id','movie title',i]]\n",
        "  genre_based_movies = genre_based_movies[genre_based_movies[i] == 1]\n",
        "  count.append(len(genre_based_movies))\n",
        "  # merged_genre_movies = pd.merge(dataset, genre_based_movies, how='inner', on='movie id')\n",
        "  # star_based_visualization(merged_genre_movies)\n",
        "df = pd.DataFrame({'Movie genre':movie_genre_list, 'Number of movies':count})\n",
        "ax = df.plot.bar(x='Movie genre', y='Number of movies', rot=60, figsize=(10, 5))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XS70qUcRIHTc"
      },
      "source": [
        "We can see that most of the movies belong to movie genre : **Drama** followed by **Comedy** then **Action, Romance and Thriller**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v6VOyzlHKW69"
      },
      "source": [
        "def star_based_visualization(dataframe):\n",
        "  dataframe['rating'].value_counts(sort=False).plot(kind='bar' ,figsize=(10,6), use_index = True, rot=0)\n",
        "  plt.title('Bar plot of rating frequency')\n",
        "  plt.xlabel('Rating')\n",
        "  plt.ylabel('Number of times a rating was given')\n",
        "  # label = list(dataframe['rating'].value_counts(sort=False))\n",
        "  plt.show()\n",
        "  print(\"Total number of users watched this Genre: \",len(dataframe))\n",
        "  print(\"  \")\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-lyP4wzTFJ4O"
      },
      "source": [
        "def recommendations_genre(genre):\n",
        "  x = genre\n",
        "  print(\"****************************     ******************************     ******************************\")\n",
        "  print(\"****************************     ****** GENRE: \", x,\" ******     ******************************\")\n",
        "  print(\"    \")\n",
        "  genre_based_movies = items_dataset[['movie id','movie title',x]]\n",
        "  genre_based_movies = genre_based_movies[genre_based_movies[x] == 1]\n",
        "  merged_genre_movies = pd.merge(dataset, genre_based_movies, how='inner', on='movie id')\n",
        "  # merged_genre_movies.head()\n",
        "\n",
        "  star_based_visualization(merged_genre_movies)\n",
        "  high_rated_movies = merged_genre_movies.groupby(['movie title']).agg({\"rating\":\"mean\"})['rating'].sort_values(ascending=False)\n",
        "  high_rated_movies = high_rated_movies.to_frame()\n",
        "  print(\"These are the top movies that can be naviely suggested to the new users for the requested movie genre:\", x, \". Recommendations based on top average ratings.\")\n",
        "  print(high_rated_movies.head(10))\n",
        "  print(\"****************************     ******************************     ******************************\")\n",
        "  popular_movies_ingenre = merged_genre_movies.groupby(['movie title']).agg({\"rating\":\"count\"})['rating'].sort_values(ascending=False)\n",
        "  popular_movies_ingenre = popular_movies_ingenre.to_frame()\n",
        "  popular_movies_ingenre.reset_index(level=0, inplace=True)\n",
        "  popular_movies_ingenre.columns = ['movie title', 'Number of Users watched']\n",
        "  print(\"These are the most popular movies which can be recommended to a new user in\",x,\"genre. Recommendations based on Popularity\")\n",
        "  print(popular_movies_ingenre.sort_values('Number of Users watched', ascending=False).head(10))\n",
        "  print(\"****************************     ******************************     ******************************\")\n",
        "  highly_rated_popular_movies = pd.merge(high_rated_movies, popular_movies_ingenre, how = 'inner', on='movie title')\n",
        "  # highly_rated_popular_movies.head(10)\n",
        "  viewer_limit = 300\n",
        "  ratings_limit = 4.0\n",
        "  count = 0\n",
        "  check = 0\n",
        "  while viewer_limit > 0 and ratings_limit > 0:\n",
        "    s = highly_rated_popular_movies[(highly_rated_popular_movies['Number of Users watched']>viewer_limit) & (highly_rated_popular_movies['rating']>=ratings_limit)]\n",
        "    if len(s) < 11:\n",
        "      if check == 0:\n",
        "        viewer_limit -= 50\n",
        "        check = 1\n",
        "      else:\n",
        "        ratings_limit -= 0.5\n",
        "        check = 0\n",
        "    else:\n",
        "      break\n",
        "  print(\"These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\")\n",
        "  print(\"These have rating more than \",ratings_limit,\" with atleast \",viewer_limit ,\" viewers.\")\n",
        "\n",
        "  print(\"**Recommendations based popularity and rating. These are top rated popular movies**\")\n",
        "  print(s)\n",
        "  print(\"****************************     ******************************     ******************************\")\n",
        "  print(\"                             \")\n",
        "  print(\"                             \")\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BLmjabNKHJe8",
        "outputId": "fbbc036c-c3d4-4422-ca3c-3b4189797ac2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "for i in movie_genre_list[1:]:\n",
        "  recommendations_genre(i)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Action  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  25589\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Action . Recommendations based on top average ratings.\n",
            "                                   rating\n",
            "movie title                              \n",
            "Star Wars (1977)                 4.358491\n",
            "Godfather, The (1972)            4.283293\n",
            "Raiders of the Lost Ark (1981)   4.252381\n",
            "Titanic (1997)                   4.245714\n",
            "Empire Strikes Back, The (1980)  4.204360\n",
            "Boot, Das (1981)                 4.203980\n",
            "Godfather: Part II, The (1974)   4.186603\n",
            "African Queen, The (1951)        4.184211\n",
            "Princess Bride, The (1987)       4.172840\n",
            "Braveheart (1995)                4.151515\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Action genre. Recommendations based on Popularity\n",
            "                       movie title  Number of Users watched\n",
            "0                 Star Wars (1977)                      583\n",
            "1        Return of the Jedi (1983)                      507\n",
            "2             Air Force One (1997)                      431\n",
            "3    Independence Day (ID4) (1996)                      429\n",
            "4   Raiders of the Lost Ark (1981)                      420\n",
            "5            Godfather, The (1972)                      413\n",
            "6                 Rock, The (1996)                      378\n",
            "7  Empire Strikes Back, The (1980)                      367\n",
            "8  Star Trek: First Contact (1996)                      365\n",
            "9                   Titanic (1997)                      350\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  4.0  with atleast  250  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                          movie title    rating  Number of Users watched\n",
            "0                    Star Wars (1977)  4.358491                      583\n",
            "1               Godfather, The (1972)  4.283293                      413\n",
            "2      Raiders of the Lost Ark (1981)  4.252381                      420\n",
            "3                      Titanic (1997)  4.245714                      350\n",
            "4     Empire Strikes Back, The (1980)  4.204360                      367\n",
            "8          Princess Bride, The (1987)  4.172840                      324\n",
            "9                   Braveheart (1995)  4.151515                      297\n",
            "11               Fugitive, The (1993)  4.044643                      336\n",
            "12                       Alien (1979)  4.034364                      291\n",
            "13          Return of the Jedi (1983)  4.007890                      507\n",
            "14  Terminator 2: Judgment Day (1991)  4.006780                      295\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Adventure  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  13753\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Adventure . Recommendations based on top average ratings.\n",
            "                                            rating\n",
            "movie title                                       \n",
            "Star Kid (1997)                           5.000000\n",
            "Star Wars (1977)                          4.358491\n",
            "Raiders of the Lost Ark (1981)            4.252381\n",
            "Lawrence of Arabia (1962)                 4.231214\n",
            "Empire Strikes Back, The (1980)           4.204360\n",
            "African Queen, The (1951)                 4.184211\n",
            "Princess Bride, The (1987)                4.172840\n",
            "Great Escape, The (1963)                  4.104839\n",
            "Treasure of the Sierra Madre, The (1948)  4.100000\n",
            "Wizard of Oz, The (1939)                  4.077236\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Adventure genre. Recommendations based on Popularity\n",
            "                                    movie title  Number of Users watched\n",
            "0                              Star Wars (1977)                      583\n",
            "1                     Return of the Jedi (1983)                      507\n",
            "2                Raiders of the Lost Ark (1981)                      420\n",
            "3                              Rock, The (1996)                      378\n",
            "4               Empire Strikes Back, The (1980)                      367\n",
            "5               Star Trek: First Contact (1996)                      365\n",
            "6                    Mission: Impossible (1996)                      344\n",
            "7     Indiana Jones and the Last Crusade (1989)                      331\n",
            "8  Willy Wonka and the Chocolate Factory (1971)                      326\n",
            "9                    Princess Bride, The (1987)                      324\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  3.5  with atleast  250  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                                     movie title  ...  Number of Users watched\n",
            "1                               Star Wars (1977)  ...                      583\n",
            "2                 Raiders of the Lost Ark (1981)  ...                      420\n",
            "4                Empire Strikes Back, The (1980)  ...                      367\n",
            "6                     Princess Bride, The (1987)  ...                      324\n",
            "11                     Return of the Jedi (1983)  ...                      507\n",
            "15     Indiana Jones and the Last Crusade (1989)  ...                      331\n",
            "20                     Dances with Wolves (1990)  ...                      256\n",
            "23                           Men in Black (1997)  ...                      303\n",
            "24                          Jurassic Park (1993)  ...                      261\n",
            "25                              Rock, The (1996)  ...                      378\n",
            "27               Star Trek: First Contact (1996)  ...                      365\n",
            "28  Willy Wonka and the Chocolate Factory (1971)  ...                      326\n",
            "\n",
            "[12 rows x 3 columns]\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Animation  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  3605\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Animation . Recommendations based on top average ratings.\n",
            "                                                      rating\n",
            "movie title                                                 \n",
            "Close Shave, A (1995)                               4.491071\n",
            "Wrong Trousers, The (1993)                          4.466102\n",
            "Wallace & Gromit: The Best of Aardman Animation...  4.447761\n",
            "Faust (1994)                                        4.200000\n",
            "Grand Day Out, A (1992)                             4.106061\n",
            "Toy Story (1995)                                    3.878319\n",
            "Aladdin (1992)                                      3.812785\n",
            "Winnie the Pooh and the Blustery Day (1968)         3.800000\n",
            "Beauty and the Beast (1991)                         3.792079\n",
            "Lion King, The (1994)                               3.781818\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Animation genre. Recommendations based on Popularity\n",
            "                              movie title  Number of Users watched\n",
            "0                        Toy Story (1995)                      452\n",
            "1                   Lion King, The (1994)                      220\n",
            "2                          Aladdin (1992)                      219\n",
            "3             Beauty and the Beast (1991)                      202\n",
            "4                         Fantasia (1940)                      174\n",
            "5  Snow White and the Seven Dwarfs (1937)                      172\n",
            "6  Beavis and Butt-head Do America (1996)                      156\n",
            "7                       Cinderella (1950)                      129\n",
            "8     Hunchback of Notre Dame, The (1996)                      127\n",
            "9        James and the Giant Peach (1996)                      126\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  2.5  with atleast  100  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                               movie title    rating  Number of Users watched\n",
            "0                    Close Shave, A (1995)  4.491071                      112\n",
            "1               Wrong Trousers, The (1993)  4.466102                      118\n",
            "5                         Toy Story (1995)  3.878319                      452\n",
            "6                           Aladdin (1992)  3.812785                      219\n",
            "8              Beauty and the Beast (1991)  3.792079                      202\n",
            "9                    Lion King, The (1994)  3.781818                      220\n",
            "10                         Fantasia (1940)  3.770115                      174\n",
            "11  Snow White and the Seven Dwarfs (1937)  3.709302                      172\n",
            "12                        Pinocchio (1940)  3.673267                      101\n",
            "15                       Cinderella (1950)  3.581395                      129\n",
            "17                            Dumbo (1941)  3.495935                      123\n",
            "20     Hunchback of Notre Dame, The (1996)  3.377953                      127\n",
            "26        James and the Giant Peach (1996)  3.126984                      126\n",
            "33  Beavis and Butt-head Do America (1996)  2.788462                      156\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Children  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  7182\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Children . Recommendations based on top average ratings.\n",
            "                                               rating\n",
            "movie title                                          \n",
            "Star Kid (1997)                              5.000000\n",
            "Wizard of Oz, The (1939)                     4.077236\n",
            "Babe (1995)                                  3.995434\n",
            "Toy Story (1995)                             3.878319\n",
            "E.T. the Extra-Terrestrial (1982)            3.833333\n",
            "Aladdin (1992)                               3.812785\n",
            "Winnie the Pooh and the Blustery Day (1968)  3.800000\n",
            "Beauty and the Beast (1991)                  3.792079\n",
            "Lion King, The (1994)                        3.781818\n",
            "Fantasia (1940)                              3.770115\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Children genre. Recommendations based on Popularity\n",
            "                                    movie title  Number of Users watched\n",
            "0                              Toy Story (1995)                      452\n",
            "1  Willy Wonka and the Chocolate Factory (1971)                      326\n",
            "2             E.T. the Extra-Terrestrial (1982)                      300\n",
            "3                      Wizard of Oz, The (1939)                      246\n",
            "4                         Lion King, The (1994)                      220\n",
            "5                                   Babe (1995)                      219\n",
            "6                                Aladdin (1992)                      219\n",
            "7                   Beauty and the Beast (1991)                      202\n",
            "8                          Fly Away Home (1996)                      180\n",
            "9                           Mary Poppins (1964)                      178\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  3.0  with atleast  150  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                                     movie title  ...  Number of Users watched\n",
            "1                       Wizard of Oz, The (1939)  ...                      246\n",
            "2                                    Babe (1995)  ...                      219\n",
            "3                               Toy Story (1995)  ...                      452\n",
            "4              E.T. the Extra-Terrestrial (1982)  ...                      300\n",
            "5                                 Aladdin (1992)  ...                      219\n",
            "7                    Beauty and the Beast (1991)  ...                      202\n",
            "8                          Lion King, The (1994)  ...                      220\n",
            "9                                Fantasia (1940)  ...                      174\n",
            "10                           Mary Poppins (1964)  ...                      178\n",
            "11        Snow White and the Seven Dwarfs (1937)  ...                      172\n",
            "15  Willy Wonka and the Chocolate Factory (1971)  ...                      326\n",
            "16                          Fly Away Home (1996)  ...                      180\n",
            "\n",
            "[12 rows x 3 columns]\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Comedy  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  29832\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Comedy . Recommendations based on top average ratings.\n",
            "                              rating\n",
            "movie title                         \n",
            "Santa with Muscles (1996)   5.000000\n",
            "Close Shave, A (1995)       4.491071\n",
            "Wrong Trousers, The (1993)  4.466102\n",
            "North by Northwest (1959)   4.284916\n",
            "Shall We Dance? (1996)      4.260870\n",
            "As Good As It Gets (1997)   4.196429\n",
            "Cinema Paradiso (1988)      4.173554\n",
            "Princess Bride, The (1987)  4.172840\n",
            "Waiting for Guffman (1996)  4.127660\n",
            "A Chef in Love (1996)       4.125000\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Comedy genre. Recommendations based on Popularity\n",
            "                                    movie title  Number of Users watched\n",
            "0                              Liar Liar (1997)                      485\n",
            "1                              Toy Story (1995)                      452\n",
            "2                     Back to the Future (1985)                      350\n",
            "3  Willy Wonka and the Chocolate Factory (1971)                      326\n",
            "4                    Princess Bride, The (1987)                      324\n",
            "5                           Forrest Gump (1994)                      321\n",
            "6        Monty Python and the Holy Grail (1974)                      316\n",
            "7                        Full Monty, The (1997)                      315\n",
            "8                           Men in Black (1997)                      303\n",
            "9                          Birdcage, The (1996)                      293\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  3.5  with atleast  250  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                                      movie title  ...  Number of Users watched\n",
            "7                      Princess Bride, The (1987)  ...                      324\n",
            "14         Monty Python and the Holy Grail (1974)  ...                      316\n",
            "45                         Full Monty, The (1997)  ...                      315\n",
            "49                 When Harry Met Sally... (1989)  ...                      290\n",
            "55                               Toy Story (1995)  ...                      452\n",
            "58                         Raising Arizona (1987)  ...                      256\n",
            "61                            Forrest Gump (1994)  ...                      321\n",
            "63                     Blues Brothers, The (1980)  ...                      251\n",
            "64                      Back to the Future (1985)  ...                      350\n",
            "79                           Groundhog Day (1993)  ...                      280\n",
            "82                            Men in Black (1997)  ...                      303\n",
            "102            Four Weddings and a Funeral (1994)  ...                      251\n",
            "106  Willy Wonka and the Chocolate Factory (1971)  ...                      326\n",
            "\n",
            "[13 rows x 3 columns]\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Crime  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  8055\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Crime . Recommendations based on top average ratings.\n",
            "                                   rating\n",
            "movie title                              \n",
            "They Made Me a Criminal (1939)   5.000000\n",
            "Usual Suspects, The (1995)       4.385768\n",
            "Letter From Death Row, A (1998)  4.333333\n",
            "Godfather, The (1972)            4.283293\n",
            "Crossfire (1947)                 4.250000\n",
            "Godfather: Part II, The (1974)   4.186603\n",
            "L.A. Confidential (1997)         4.161616\n",
            "Fargo (1996)                     4.155512\n",
            "Laura (1944)                     4.100000\n",
            "Once Were Warriors (1994)        4.064516\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Crime genre. Recommendations based on Popularity\n",
            "                      movie title  Number of Users watched\n",
            "0                    Fargo (1996)                      508\n",
            "1           Godfather, The (1972)                      413\n",
            "2             Pulp Fiction (1994)                      394\n",
            "3        L.A. Confidential (1997)                      297\n",
            "4      Usual Suspects, The (1995)                      267\n",
            "5               Sting, The (1973)                      241\n",
            "6            Seven (Se7en) (1995)                      236\n",
            "7               GoodFellas (1990)                      226\n",
            "8                     Heat (1995)                      223\n",
            "9  Godfather: Part II, The (1974)                      209\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  3.0  with atleast  200  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                       movie title    rating  Number of Users watched\n",
            "1       Usual Suspects, The (1995)  4.385768                      267\n",
            "3            Godfather, The (1972)  4.283293                      413\n",
            "5   Godfather: Part II, The (1974)  4.186603                      209\n",
            "6         L.A. Confidential (1997)  4.161616                      297\n",
            "7                     Fargo (1996)  4.155512                      508\n",
            "10             Pulp Fiction (1994)  4.060914                      394\n",
            "11               Sting, The (1973)  4.058091                      241\n",
            "19               GoodFellas (1990)  3.951327                      226\n",
            "21            Seven (Se7en) (1995)  3.847458                      236\n",
            "31                     Heat (1995)  3.569507                      223\n",
            "40                   Batman (1989)  3.427861                      201\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Documentary  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  758\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Documentary . Recommendations based on top average ratings.\n",
            "                                                      rating\n",
            "movie title                                                 \n",
            "Great Day in Harlem, A (1994)                       5.000000\n",
            "Marlene Dietrich: Shadow and Light (1996)           5.000000\n",
            "Maya Lin: A Strong Clear Vision (1994)              4.500000\n",
            "Everest (1998)                                      4.500000\n",
            "Hoop Dreams (1994)                                  4.094017\n",
            "Paradise Lost: The Child Murders at Robin Hood ...  4.050000\n",
            "When We Were Kings (1996)                           4.045455\n",
            "Nico Icon (1995)                                    4.000000\n",
            "Wonderful, Horrible Life of Leni Riefenstahl, T...  4.000000\n",
            "Gate of Heavenly Peace, The (1995)                  4.000000\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Documentary genre. Recommendations based on Popularity\n",
            "                                movie title  Number of Users watched\n",
            "0                        Hoop Dreams (1994)                      117\n",
            "1                              Crumb (1994)                       81\n",
            "2              Celluloid Closet, The (1995)                       56\n",
            "3                Looking for Richard (1996)                       55\n",
            "4                      Koyaanisqatsi (1983)                       53\n",
            "5                 When We Were Kings (1996)                       44\n",
            "6                Thin Blue Line, The (1988)                       35\n",
            "7       Fast, Cheap & Out of Control (1997)                       32\n",
            "8                   Paris Is Burning (1990)                       27\n",
            "9  Microcosmos: Le peuple de l'herbe (1996)                       24\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  1.5  with atleast  0  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                     movie title    rating  Number of Users watched\n",
            "4             Hoop Dreams (1994)  4.094017                      117\n",
            "13  Celluloid Closet, The (1995)  3.892857                       56\n",
            "16                  Crumb (1994)  3.790123                       81\n",
            "20    Looking for Richard (1996)  3.727273                       55\n",
            "23          Koyaanisqatsi (1983)  3.490566                       53\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Drama  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  39895\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Drama . Recommendations based on top average ratings.\n",
            "                                                     rating\n",
            "movie title                                                \n",
            "Prefontaine (1997)                                 5.000000\n",
            "Entertaining Angels: The Dorothy Day Story (1996)  5.000000\n",
            "Someone Else's America (1995)                      5.000000\n",
            "They Made Me a Criminal (1939)                     5.000000\n",
            "Aiqing wansui (1994)                               5.000000\n",
            "Saint of Fort Washington, The (1993)               5.000000\n",
            "Pather Panchali (1955)                             4.625000\n",
            "Some Mother's Son (1996)                           4.500000\n",
            "Anna (1996)                                        4.500000\n",
            "Schindler's List (1993)                            4.466443\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Drama genre. Recommendations based on Popularity\n",
            "                        movie title  Number of Users watched\n",
            "0                    Contact (1997)                      509\n",
            "1                      Fargo (1996)                      508\n",
            "2       English Patient, The (1996)                      481\n",
            "3             Godfather, The (1972)                      413\n",
            "4               Pulp Fiction (1994)                      394\n",
            "5             Twelve Monkeys (1995)                      392\n",
            "6  Silence of the Lambs, The (1991)                      390\n",
            "7              Jerry Maguire (1996)                      384\n",
            "8                Chasing Amy (1997)                      379\n",
            "9   Empire Strikes Back, The (1980)                      367\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  4.0  with atleast  250  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                               movie title    rating  Number of Users watched\n",
            "9                  Schindler's List (1993)  4.466443                      298\n",
            "11        Shawshank Redemption, The (1994)  4.445230                      283\n",
            "18  One Flew Over the Cuckoo's Nest (1975)  4.291667                      264\n",
            "19        Silence of the Lambs, The (1991)  4.289744                      390\n",
            "20                   Godfather, The (1972)  4.283293                      413\n",
            "24                          Titanic (1997)  4.245714                      350\n",
            "26         Empire Strikes Back, The (1980)  4.204360                      367\n",
            "34                          Amadeus (1984)  4.163043                      276\n",
            "35                            Fargo (1996)  4.155512                      508\n",
            "37                       Braveheart (1995)  4.151515                      297\n",
            "54                     Pulp Fiction (1994)  4.060914                      394\n",
            "63            Sense and Sensibility (1995)  4.011194                      268\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Fantasy  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  1352\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Fantasy . Recommendations based on top average ratings.\n",
            "                                       rating\n",
            "movie title                                  \n",
            "Star Kid (1997)                      5.000000\n",
            "E.T. the Extra-Terrestrial (1982)    3.833333\n",
            "Heavenly Creatures (1994)            3.671429\n",
            "20,000 Leagues Under the Sea (1954)  3.500000\n",
            "Jumanji (1995)                       3.312500\n",
            "Mask, The (1994)                     3.193798\n",
            "Dragonheart (1996)                   3.082278\n",
            "Warriors of Virtue (1997)            3.000000\n",
            "FairyTale: A True Story (1997)       2.966667\n",
            "Escape to Witch Mountain (1975)      2.966667\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Fantasy genre. Recommendations based on Popularity\n",
            "                           movie title  Number of Users watched\n",
            "0    E.T. the Extra-Terrestrial (1982)                      300\n",
            "1          Nutty Professor, The (1996)                      163\n",
            "2                   Dragonheart (1996)                      158\n",
            "3                     Mask, The (1994)                      129\n",
            "4                       Jumanji (1995)                       96\n",
            "5                     Space Jam (1996)                       93\n",
            "6  20,000 Leagues Under the Sea (1954)                       72\n",
            "7            Heavenly Creatures (1994)                       70\n",
            "8                       Flubber (1997)                       53\n",
            "9   Indian in the Cupboard, The (1995)                       39\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  1.5  with atleast  0  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                            movie title    rating  Number of Users watched\n",
            "1     E.T. the Extra-Terrestrial (1982)  3.833333                      300\n",
            "2             Heavenly Creatures (1994)  3.671429                       70\n",
            "3   20,000 Leagues Under the Sea (1954)  3.500000                       72\n",
            "4                        Jumanji (1995)  3.312500                       96\n",
            "5                      Mask, The (1994)  3.193798                      129\n",
            "6                    Dragonheart (1996)  3.082278                      158\n",
            "10          Nutty Professor, The (1996)  2.914110                      163\n",
            "12                     Space Jam (1996)  2.774194                       93\n",
            "13                       Flubber (1997)  2.754717                       53\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Film-Noir  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  1733\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Film-Noir . Recommendations based on top average ratings.\n",
            "                                    rating\n",
            "movie title                               \n",
            "Manchurian Candidate, The (1962)  4.259542\n",
            "Crossfire (1947)                  4.250000\n",
            "Maltese Falcon, The (1941)        4.210145\n",
            "Sunset Blvd. (1950)               4.200000\n",
            "L.A. Confidential (1997)          4.161616\n",
            "Blade Runner (1982)               4.138182\n",
            "Chinatown (1974)                  4.136054\n",
            "Notorious (1946)                  4.115385\n",
            "Laura (1944)                      4.100000\n",
            "Big Sleep, The (1946)             4.027397\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Film-Noir genre. Recommendations based on Popularity\n",
            "                        movie title  Number of Users watched\n",
            "0          L.A. Confidential (1997)                      297\n",
            "1               Blade Runner (1982)                      275\n",
            "2                  Chinatown (1974)                      147\n",
            "3        Maltese Falcon, The (1941)                      138\n",
            "4  Manchurian Candidate, The (1962)                      131\n",
            "5              Grifters, The (1990)                       89\n",
            "6                  Cape Fear (1962)                       86\n",
            "7           Mulholland Falls (1996)                       82\n",
            "8             Big Sleep, The (1946)                       73\n",
            "9                    Hoodlum (1997)                       73\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  2.0  with atleast  50  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                         movie title    rating  Number of Users watched\n",
            "0   Manchurian Candidate, The (1962)  4.259542                      131\n",
            "2         Maltese Falcon, The (1941)  4.210145                      138\n",
            "3                Sunset Blvd. (1950)  4.200000                       65\n",
            "4           L.A. Confidential (1997)  4.161616                      297\n",
            "5                Blade Runner (1982)  4.138182                      275\n",
            "6                   Chinatown (1974)  4.136054                      147\n",
            "7                   Notorious (1946)  4.115385                       52\n",
            "9              Big Sleep, The (1946)  4.027397                       73\n",
            "14                  Cape Fear (1962)  3.523256                       86\n",
            "16              Grifters, The (1990)  3.483146                       89\n",
            "17      Devil in a Blue Dress (1995)  3.385965                       57\n",
            "19                    Hoodlum (1997)  2.931507                       73\n",
            "20           Mulholland Falls (1996)  2.878049                       82\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Horror  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  5317\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Horror . Recommendations based on top average ratings.\n",
            "                                                      rating\n",
            "movie title                                                 \n",
            "Psycho (1960)                                       4.100418\n",
            "Alien (1979)                                        4.034364\n",
            "Young Frankenstein (1974)                           3.945000\n",
            "Braindead (1992)                                    3.857143\n",
            "Shining, The (1980)                                 3.825243\n",
            "Birds, The (1963)                                   3.808642\n",
            "Jaws (1975)                                         3.775000\n",
            "Night Flier (1997)                                  3.714286\n",
            "Bride of Frankenstein (1935)                        3.608696\n",
            "Nosferatu (Nosferatu, eine Symphonie des Grauen...  3.555556\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Horror genre. Recommendations based on Popularity\n",
            "                         movie title  Number of Users watched\n",
            "0                      Scream (1996)                      478\n",
            "1                       Alien (1979)                      291\n",
            "2                        Jaws (1975)                      280\n",
            "3                      Psycho (1960)                      239\n",
            "4                Shining, The (1980)                      206\n",
            "5          Young Frankenstein (1974)                      200\n",
            "6       Devil's Advocate, The (1997)                      188\n",
            "7                  Birds, The (1963)                      162\n",
            "8  Interview with the Vampire (1994)                      137\n",
            "9         Alien: Resurrection (1997)                      124\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  2.5  with atleast  100  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                          movie title    rating  Number of Users watched\n",
            "0                       Psycho (1960)  4.100418                      239\n",
            "1                        Alien (1979)  4.034364                      291\n",
            "2           Young Frankenstein (1974)  3.945000                      200\n",
            "4                 Shining, The (1980)  3.825243                      206\n",
            "5                   Birds, The (1963)  3.808642                      162\n",
            "6                         Jaws (1975)  3.775000                      280\n",
            "12       Devil's Advocate, The (1997)  3.515957                      188\n",
            "13                      Carrie (1976)  3.504132                      121\n",
            "15                      Scream (1996)  3.441423                      478\n",
            "16            Army of Darkness (1993)  3.431034                      116\n",
            "21            Frighteners, The (1996)  3.234783                      115\n",
            "22                    Scream 2 (1997)  3.216981                      106\n",
            "24  Interview with the Vampire (1994)  3.182482                      137\n",
            "25  Nightmare on Elm Street, A (1984)  3.171171                      111\n",
            "26       Bram Stoker's Dracula (1992)  3.158333                      120\n",
            "28                  Craft, The (1996)  3.115385                      104\n",
            "29         Alien: Resurrection (1997)  3.096774                      124\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Musical  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  4954\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Musical . Recommendations based on top average ratings.\n",
            "                                rating\n",
            "movie title                           \n",
            "Wizard of Oz, The (1939)      4.077236\n",
            "Top Hat (1935)                4.047619\n",
            "Damsel in Distress, A (1937)  4.000000\n",
            "Singin' in the Rain (1952)    3.992701\n",
            "This Is Spinal Tap (1984)     3.905759\n",
            "Gay Divorcee, The (1934)      3.866667\n",
            "Blues Brothers, The (1980)    3.836653\n",
            "My Fair Lady (1964)           3.816000\n",
            "Aladdin (1992)                3.812785\n",
            "Beauty and the Beast (1991)   3.792079\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Musical genre. Recommendations based on Popularity\n",
            "                   movie title  Number of Users watched\n",
            "0                 Evita (1996)                      259\n",
            "1   Blues Brothers, The (1980)                      251\n",
            "2     Wizard of Oz, The (1939)                      246\n",
            "3   Sound of Music, The (1965)                      222\n",
            "4        Lion King, The (1994)                      220\n",
            "5               Aladdin (1992)                      219\n",
            "6  Beauty and the Beast (1991)                      202\n",
            "7    This Is Spinal Tap (1984)                      191\n",
            "8          Mary Poppins (1964)                      178\n",
            "9              Fantasia (1940)                      174\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  3.0  with atleast  150  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                               movie title    rating  Number of Users watched\n",
            "0                 Wizard of Oz, The (1939)  4.077236                      246\n",
            "4                This Is Spinal Tap (1984)  3.905759                      191\n",
            "6               Blues Brothers, The (1980)  3.836653                      251\n",
            "8                           Aladdin (1992)  3.812785                      219\n",
            "9              Beauty and the Beast (1991)  3.792079                      202\n",
            "10                   Lion King, The (1994)  3.781818                      220\n",
            "11                         Fantasia (1940)  3.770115                      174\n",
            "12              Sound of Music, The (1965)  3.765766                      222\n",
            "14                     Mary Poppins (1964)  3.724719                      178\n",
            "16  Snow White and the Seven Dwarfs (1937)  3.709302                      172\n",
            "35                           Grease (1978)  3.347059                      170\n",
            "38         Everyone Says I Love You (1996)  3.273810                      168\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Mystery  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  5245\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Mystery . Recommendations based on top average ratings.\n",
            "                               rating\n",
            "movie title                          \n",
            "Rear Window (1954)           4.387560\n",
            "Third Man, The (1949)        4.333333\n",
            "Vertigo (1958)               4.251397\n",
            "Maltese Falcon, The (1941)   4.210145\n",
            "Amadeus (1984)               4.163043\n",
            "L.A. Confidential (1997)     4.161616\n",
            "Thin Man, The (1934)         4.150000\n",
            "Chinatown (1974)             4.136054\n",
            "Laura (1944)                 4.100000\n",
            "Arsenic and Old Lace (1944)  4.078261\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Mystery genre. Recommendations based on Popularity\n",
            "                    movie title  Number of Users watched\n",
            "0    Mission: Impossible (1996)                      344\n",
            "1      L.A. Confidential (1997)                      297\n",
            "2      Conspiracy Theory (1997)                      295\n",
            "3                Amadeus (1984)                      276\n",
            "4  2001: A Space Odyssey (1968)                      259\n",
            "5              Game, The (1997)                      251\n",
            "6         Murder at 1600 (1997)                      218\n",
            "7            Rear Window (1954)                      209\n",
            "8  Devil's Advocate, The (1997)                      188\n",
            "9              Lone Star (1996)                      187\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  3.0  with atleast  150  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                     movie title    rating  Number of Users watched\n",
            "0             Rear Window (1954)  4.387560                      209\n",
            "2                 Vertigo (1958)  4.251397                      179\n",
            "4                 Amadeus (1984)  4.163043                      276\n",
            "5       L.A. Confidential (1997)  4.161616                      297\n",
            "10              Lone Star (1996)  4.053476                      187\n",
            "14  2001: A Space Odyssey (1968)  3.969112                      259\n",
            "23              Game, The (1997)  3.593625                      251\n",
            "27  Devil's Advocate, The (1997)  3.515957                      188\n",
            "28      Conspiracy Theory (1997)  3.423729                      295\n",
            "31               Cop Land (1997)  3.377143                      175\n",
            "36    Mission: Impossible (1996)  3.313953                      344\n",
            "43         Murder at 1600 (1997)  3.087156                      218\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Romance  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  19461\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Romance . Recommendations based on top average ratings.\n",
            "                                   rating\n",
            "movie title                              \n",
            "Casablanca (1942)                4.456790\n",
            "Star Wars (1977)                 4.358491\n",
            "Titanic (1997)                   4.245714\n",
            "Empire Strikes Back, The (1980)  4.204360\n",
            "Affair to Remember, An (1957)    4.192308\n",
            "African Queen, The (1951)        4.184211\n",
            "Cinema Paradiso (1988)           4.173554\n",
            "Princess Bride, The (1987)       4.172840\n",
            "Notorious (1946)                 4.115385\n",
            "Philadelphia Story, The (1940)   4.115385\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Romance genre. Recommendations based on Popularity\n",
            "                       movie title  Number of Users watched\n",
            "0                 Star Wars (1977)                      583\n",
            "1        Return of the Jedi (1983)                      507\n",
            "2      English Patient, The (1996)                      481\n",
            "3             Jerry Maguire (1996)                      384\n",
            "4               Chasing Amy (1997)                      379\n",
            "5  Empire Strikes Back, The (1980)                      367\n",
            "6                   Titanic (1997)                      350\n",
            "7       Princess Bride, The (1987)                      324\n",
            "8              Forrest Gump (1994)                      321\n",
            "9                Saint, The (1997)                      316\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  3.5  with atleast  250  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                           movie title    rating  Number of Users watched\n",
            "1                     Star Wars (1977)  4.358491                      583\n",
            "2                       Titanic (1997)  4.245714                      350\n",
            "3      Empire Strikes Back, The (1980)  4.204360                      367\n",
            "7           Princess Bride, The (1987)  4.172840                      324\n",
            "19        Sense and Sensibility (1995)  4.011194                      268\n",
            "20           Return of the Jedi (1983)  4.007890                      507\n",
            "40      When Harry Met Sally... (1989)  3.910345                      290\n",
            "44                 Forrest Gump (1994)  3.853583                      321\n",
            "45                  Chasing Amy (1997)  3.839050                      379\n",
            "54                Groundhog Day (1993)  3.764286                      280\n",
            "60                Jerry Maguire (1996)  3.710938                      384\n",
            "64            Leaving Las Vegas (1995)  3.697987                      298\n",
            "67  Four Weddings and a Funeral (1994)  3.661355                      251\n",
            "69         English Patient, The (1996)  3.656965                      481\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Sci-Fi  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  12730\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Sci-Fi . Recommendations based on top average ratings.\n",
            "                                                      rating\n",
            "movie title                                                 \n",
            "Star Kid (1997)                                     5.000000\n",
            "Star Wars (1977)                                    4.358491\n",
            "Dr. Strangelove or: How I Learned to Stop Worry...  4.252577\n",
            "Empire Strikes Back, The (1980)                     4.204360\n",
            "Blade Runner (1982)                                 4.138182\n",
            "Alien (1979)                                        4.034364\n",
            "Return of the Jedi (1983)                           4.007890\n",
            "Terminator 2: Judgment Day (1991)                   4.006780\n",
            "2001: A Space Odyssey (1968)                        3.969112\n",
            "Aliens (1986)                                       3.947183\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Sci-Fi genre. Recommendations based on Popularity\n",
            "                       movie title  Number of Users watched\n",
            "0                 Star Wars (1977)                      583\n",
            "1                   Contact (1997)                      509\n",
            "2        Return of the Jedi (1983)                      507\n",
            "3    Independence Day (ID4) (1996)                      429\n",
            "4            Twelve Monkeys (1995)                      392\n",
            "5  Empire Strikes Back, The (1980)                      367\n",
            "6  Star Trek: First Contact (1996)                      365\n",
            "7        Back to the Future (1985)                      350\n",
            "8              Men in Black (1997)                      303\n",
            "9           Terminator, The (1984)                      301\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  3.5  with atleast  250  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                          movie title    rating  Number of Users watched\n",
            "1                    Star Wars (1977)  4.358491                      583\n",
            "3     Empire Strikes Back, The (1980)  4.204360                      367\n",
            "4                 Blade Runner (1982)  4.138182                      275\n",
            "5                        Alien (1979)  4.034364                      291\n",
            "6           Return of the Jedi (1983)  4.007890                      507\n",
            "7   Terminator 2: Judgment Day (1991)  4.006780                      295\n",
            "8        2001: A Space Odyssey (1968)  3.969112                      259\n",
            "9                       Aliens (1986)  3.947183                      284\n",
            "11             Terminator, The (1984)  3.933555                      301\n",
            "15          Back to the Future (1985)  3.834286                      350\n",
            "16  E.T. the Extra-Terrestrial (1982)  3.833333                      300\n",
            "19                     Contact (1997)  3.803536                      509\n",
            "20              Twelve Monkeys (1995)  3.798469                      392\n",
            "23                Men in Black (1997)  3.745875                      303\n",
            "24               Jurassic Park (1993)  3.720307                      261\n",
            "25    Star Trek: First Contact (1996)  3.660274                      365\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Thriller  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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DGZ+zR16ZJEnSDNdlMsEC4DTgxVX1nyOuR5IkSU2XZ30+ezIKkSRJ0orGDWpJTq+qw9opz+HncYbBbc+eMfLqJEmSZrCJRtSObu8HTUYhkiRJWtG4Qa09Z5OqunbyypEkSdKY1V6jluROVjz1CXA7sAR4e1VdPYrCJEmSZrousz4/DlzP4DmfAQ4HngxcxGBG6PNHVZwkSdJM1uWGtwdX1Weq6s6quqOqTmJwq47TgK1GXJ8kSdKM1SWo3ZPksCQbtNdhwL3ts5VPiUqSJGkd6RLUXgO8DrgZuKktvzbJJsCbR1ibJEnSjNblhrdXAy8d5+PvrdtyJEmSNKbTQ9klSZI0+QxqkiRJPWVQkyRJ6qnVBrUkRyfZIgMnJ7koyX6TUZwkSdJM1mVE7Y+r6g5gPwb3TXsdcMJIq5IkSVKnoJb2/hLgn6vqsqE2SZIkjUiXoHZhkn9jENS+lWRz4MHRliVJkqQuz/o8EtgduLqq7kmyDXDEaMuSJElSlxvePpjk58DvJHncJNQkSZIkOgS1JG8EjgZmAxcD+wA/AF442tIkSZJmti7XqB0NPAu4tqpeAOwB3DbSqiRJktQpqN1bVfcCJHlsVf0UeOpoy5IkSVKXyQTXJ5kFfAVYnORW4NrRliVJkqQukwn+sC2+L8k5wJbAN0dalSRJkjpNJjge+C7w/ar6zuhLkiRJEnS7Ru1q4NXAkiTnJ/lIkkO6dJ7kmiSXJrk4yZLWtnWSxUmuau9btfYkOTHJ0iSXJNlzqJ95bfurksxbi+8pSZI07aw2qFXVP1XVHwMvAD4PvLK9d/WCqtq9qua29WOAs6tqV+Dstg5wALBre80HPg2DYAccC+wN7AUcOxbuJEmS1merDWpJ/jHJ9xkEp42AVzB4OPvaOgRY2JYXAocOtX+uBs4DZiXZAXgxsLiqllfVrcBiYP9HcXxJkqRpocupz22ADRncO2058Iuqur9j/wX8W5ILk8xvbdtX1Q1t+UZg+7a8I3Dd0L7Xt7bx2iVJktZrnWd9JvldBqNb5yTZsKpmd+j/uVW1LMlvMbi1x09X6ruS1NoUvrIWBOcD7LzzzuuiS0mSpCnVZdbnQcDvA88DZgHfBv5Pl86rall7vznJlxlcY3ZTkh2q6oZ2avPmtvkyYKeh3We3tmXA81dqP3cVxzoJOAlg7ty56yT8SZIkTaUupz73By4CXl5Vv1tVR1TVgtXtlGTTJJuPLQP7AT8BFgFjMzfnAV9ty4uA17fZn/sAt7dTpN8C9kuyVZtEsF9rkyRJWq91OfX55rXse3vgy0nGjvOFqvpmkguA05McyeAJB4e17c8CXgIsBe4BjmjHX97u5XZB2+64qlq+ljVJkiRNG10eIbVWqupq4JmraP8lsO8q2gs4apy+FgCrHcWTJElan3Q59SlJkqQpYFCTJEnqqS6zPi9lcD+0YbcDS4APtFOZkiRJWse6XKP2DeAB4Att/XDg8QxuVvtZ4KUjqUySJGmG6xLU/r+q2nNo/dIkF1XVnkleO6rCJEmSZrou16htmGSvsZUkz2LwSCmAro+SkiRJ0hrqMqL2RmBBks2AAHcAb2w3sf3QKIuTJEmaybrc8PYC4OlJtmzrtw99fPqoCpMkSZrpusz6fCzwcmAOsFF70gBVddxIK5MkSZrhupz6/CqD23FcCNw32nIkSZI0pktQm11V+4+8EkmSJK2gy6zP7yd5+sgrkSRJ0gq6jKg9F3hDkp8zOPUZBs9Qf8ZIK5MkSZrhugS1A0ZehSRJkh5h3KCWZIuqugO4cxLrkSRJUjPRiNoXgIMYzPYsBqc8xxTw2yOsS5IkacYbN6hV1UHtfZfJK0eSJEljVjvrM8nZXdokSZK0bk10jdrjgMcD2ybZiodPfW4B7DgJtUmSJM1oE12j9ibgrcATGVynNhbU7gA+OeK6JEmSZryJrlH7BPCJJG+pqr+dxJokSZJEh/uoVdXfJvk9YDfgcUPtnxtlYZIkSTPdaoNakmOB5zMIamcxuAHu9wCDmiRJ0gh1eTLBK4BnAj+qqiOSbA98frRlSZKkPptzzJlTXcLIXHPCgVNdwkO6PJT9V1X1IHB/ki2Am4GdRluWJEmSuoyoLUkyC/gHBrM/7wJ+MNKqJEmSNHFQSxLgQ1V1G/D3Sb4JbFFVl0xKdZIkSTPYhEGtqirJWcDT2/o1k1GUJEmSul2jdlGSZ428EkmSJK2gyzVqewOvSXItcDeDJxRUVT1jpJVJkiTNcF2C2otHXoUkSZIeocuTCa6djEIkSZK0oi7XqD0qSTZM8qMkX2/ruyT5YZKlSU5L8pjW/ti2vrR9Pmeoj3e29iuTOMInSZJmhJEHNeBo4Iqh9Q8DH6uqpwC3Ake29iOBW1v7x9p2JNkNOBx4GrA/8HdJNpyEuiVJkqbUSINaktnAgcA/tvUALwTOaJssBA5ty4e0ddrn+7btDwFOrar7qurnwFJgr1HWLUmS1AerDWpJ9klyQZK7kvw6yQNJ7ujY/8eBdwAPtvVtgNuq6v62fj2wY1veEbgOoH1+e9v+ofZV7CNJkrTe6jKi9kng1cBVwCbAG4FPrW6nJAcBN1fVhY+qwo6SzE+yJMmSW265ZTIOKUmSNFKdTn1W1VJgw6p6oKr+icG1YqvzHODgJNcApzI45fkJYFaSsdmms4FlbXkZ7WHv7fMtgV8Ot69in+EaT6qquVU1d7vttuvytSRJknqtS1C7p83MvDjJXyf5iy77VdU7q2p2Vc1hMBng21X1GuAc4BVts3nAV9vyorZO+/zbVVWt/fA2K3QXYFfg/G5fT5IkafrqEtRe17Z7M4MnE+wEvPxRHPMvgbclWcrgGrSTW/vJwDat/W3AMQBVdRlwOnA58E3gqKp64FEcX5IkaVpYkxve3gu8f20OUlXnAue25atZxazNqroXeOU4+38Q+ODaHFuSJGm6moz7qEmSJGktGNQkSZJ6ao2CWpINkmwxqmIkSZL0sC43vP1Cki2SbAr8BLg8yf8cfWmSJEkzW5cRtd2q6g4Gj3r6BrALg5mgkiRJGqEuQW3jJBszCGqLquo3QI22LEmSJHUJap8BrgE2Bb6b5ElA12d9SpIkaS11uY/aicCJQ03XJnnB6EqSJEkSdJtMsH2Sk5N8o63vxsOPepIkSdKIdDn1+VngW8AT2/rPgLeOqiBJkiQNdAlq21bV6cCDAFV1P+CzNiVJkkasS1C7O8k2tJmeSfYBbh9pVZIkSVr9ZALgbcAi4MlJ/i+wHfCKkVYlSZKkTrM+L0ryB8BTgQBXtnupSZIkaYRWG9SSbAi8BJjTtt8vCVX10RHXJkmSNKN1OfX5NeBe4FLahAJJkiSNXpegNruqnjHySiRJkrSCLrM+v5Fkv5FXIkmSpBV0GVE7D/hykg2A3zCYUFBVtcVIK5MkSZrhugS1jwLPBi6tqhpxPZIkSWq6nPq8DviJIU2SJGlydRlRuxo4tz2U/b6xRm/PIUmSNFpdgtrP2+sx7SVJkqRJ0OXJBO+fjEIkSZK0onGDWpKPV9Vbk3yN9kD2YVV18EgrkyRJmuEmGlH75/b+N5NRiCRJklY0blCrqgvb4u5V9Ynhz5IcDXxnlIVJkiTNdF1uzzFvFW1vWMd1SJIkaSUTXaP2auCPgF2SLBr6aHNg+agLkyRJmukmukbt+8ANwLbAR4ba7wQuGWVRkiRJmvgatWuBaxk8PkqSJEmTrMs1apIkSZoCIwtqSR6X5PwkP05yWZL3t/ZdkvwwydIkpyV5TGt/bFtf2j6fM9TXO1v7lUlePKqaJUmS+mTcoJbk7Pb+4bXs+z7ghVX1TGB3YP8k+wAfBj5WVU8BbgWObNsfCdza2j/WtiPJbsDhwNOA/YG/S7LhWtYkSZI0bUw0orZDkv8GHJxkjyR7Dr9W13EN3NVWN26vAl4InNHaFwKHtuVD2jrt832TpLWfWlX3VdXPgaXAXmvwHSVJkqaliWZ9vhd4DzAb+OhKn40Frgm1ka8LgacAnwL+A7itqu5vm1wP7NiWdwSuA6iq+5PcDmzT2s8b6nZ4n+FjzQfmA+y8886rK02SJKn3Jpr1eQZwRpL3VNXxa9N5VT0A7J5kFvBl4L+sXZmdjnUScBLA3LlzH/FsUkmSpOlmohE1AKrq+CQHA89rTedW1dfX5CBVdVuScxjc6mNWko3aqNpsYFnbbBmwE3B9ko2ALYFfDrWPGd5HkiRpvbXaWZ9JPgQcDVzeXkcn+asO+23XRtJIsgnwIuAK4BzgFW2zecBX2/IiHn5c1SuAb1dVtfbD26zQXYBdgfO7fT1JkqTpa7UjasCBDB7M/iBAkoXAj4B3rWa/HYCF7Tq1DYDTq+rrSS4HTk3ygdbPyW37k4F/TrKUwSOqDgeoqsuSnM4gJN4PHNVOqUqSJK3XugQ1gFk8/HzPLbvsUFWXAHusov1qVjFrs6ruBV45Tl8fBD7YsVZJkqT1Qpeg9iHgR+0aszC4Vu2YkVYlSZKkTpMJTklyLvCs1vSXVXXjSKuSJElSt1OfVXUDg4v6JUmSNEl8KLskSVJPGdQkSZJ6asKglmTDJD+drGIkSZL0sAmDWrtf2ZVJfHimJEnSJOsymWAr4LIk5wN3jzVW1cEjq0qSJEmdgtp7Rl6FJEmSHqHLfdS+k+RJwK5V9e9JHg9sOPrSJEmSZrbVBrUkfwLMB7YGngzsCPw9sO9oS5Mmx5xjzpzqEkbqmhMOnOoSJElrqcvtOY4CngPcAVBVVwG/NcqiJEmS1C2o3VdVvx5bSbIRUKMrSZIkSdAtqH0nybuATZK8CPgi8LXRliVJkqQuQe0Y4BbgUuBNwFnAu0dZlCRJkrrN+nwwyULghwxOeV5ZVZ76lCRJGrEusz4PZDDL8z+AALskeVNVfWPUxUmSJM1kXW54+xHgBVW1FCDJk4EzAYOaJEnSCHW5Ru3OsZDWXA3cOaJ6JEmS1Iw7opbkZW1xSZKzgNMZXKP2SuCCSahNkiRpRpvo1OdLh5ZvAv6gLd8CbDKyiiRJkgRMENSq6ojJLESSJEkr6jLrcxfgLcCc4e2r6uDRlSVJkqQusz6/ApzM4GkED462HEmSJI3pEtTuraoTR16JJEmSVtAlqH0iybHAvwH3jTVW1UUjq0qSJEmdgtrTgdcBL+ThU5/V1iVJkjQiXYLaK4Hfrqpfj7oYSZIkPazLkwl+AswadSGSJElaUZcRtVnAT5NcwIrXqHl7DkmSpBHqEtSOHXkVkiRJeoTVBrWq+s5kFCJJkqQVrfYatSR3Jrmjve5N8kCSOzrst1OSc5JcnuSyJEe39q2TLE5yVXvfqrUnyYlJlia5JMmeQ33Na9tflWTeo/nCkiRJ08Vqg1pVbV5VW1TVFgwexv5y4O869H0/8Paq2g3YBzgqyW7AMcDZVbUrcHZbBzgA2LW95gOfhkGwY3D6dW9gL+DYsXAnSZK0Pusy6/MhNfAV4MUdtr1h7Ka4VXUncAWwI3AIsLBtthA4tC0fAnyuHeM8YFaSHdqxFlfV8qq6FVgM7L8mdUuSJE1HXR7K/rKh1Q2AucC9a3KQJHOAPYAfAttX1Q3toxuB7dvyjsB1Q7td39rGa1/5GPMZjMSx8847r0l5kiRJvdRl1udLh5bvB65hMPrVSZLNgC8Bb62qO5I89FlVVZLq2tdEquok4CSAuXPnrpM+JUmSplKXWZ9HrG3nSTZmENL+par+tTXflGSHqrqhndq8ubUvA3Ya2n12a1sGPH+l9nPXtiZJkqTpYtygluS9E+xXVXX8RB1nMHR2MnBFVX106KNFwDzghPb+1aH2Nyc5lcHEgdtbmPsW8FdDEwj2A9450bElSZLWBxONqN29irZNgSOBbYAJgxrwHAYPc780ycWt7V0MAtrpSY4ErgUOa5+dBbwEWArcAxwBUFXLkxwPXNC2O66qlq/m2JIkSdPeuEGtqj4ytpxkc+BoBuHpVOAj4+03tP/3gIzz8b6r2L6Ao8bpawGwYHXHlCRJWp9MeI1au4fZ24DXMLiVxp7tFhmSJEkasYmuUfvfwMsYzKR8elXdNWlVSZIkacIb3r4deCLwbuA/hx4jdWeXR0hJkiTp0ZnoGrU1emqBJEmS1i3DmCRJUk8Z1CRJknrKoCZJkrRD4jcAAAgaSURBVNRTBjVJkqSeMqhJkiT1lEFNkiSppwxqkiRJPWVQkyRJ6imDmiRJUk8Z1CRJknrKoCZJktRTBjVJkqSeMqhJkiT1lEFNkiSppwxqkiRJPWVQkyRJ6imDmiRJUk8Z1CRJknrKoCZJktRTBjVJkqSeMqhJkiT11EZTXcD6YM4xZ051CSN1zQkHTnUJkiTNSI6oSZIk9ZRBTZIkqacMapIkST1lUJMkSeopg5okSVJPGdQkSZJ6amRBLcmCJDcn+clQ29ZJFie5qr1v1dqT5MQkS5NckmTPoX3mte2vSjJvVPVKkiT1zShH1D4L7L9S2zHA2VW1K3B2Wwc4ANi1veYDn4ZBsAOOBfYG9gKOHQt3kiRJ67uRBbWq+i6wfKXmQ4CFbXkhcOhQ++dq4DxgVpIdgBcDi6tqeVXdCizmkeFPkiRpvTTZ16htX1U3tOUbge3b8o7AdUPbXd/axmt/hCTzkyxJsuSWW25Zt1VLkiRNgSmbTFBVBdQ67O+kqppbVXO32267ddWtJEnSlJnsoHZTO6VJe7+5tS8DdhrabnZrG69dkiRpvTfZQW0RMDZzcx7w1aH217fZn/sAt7dTpN8C9kuyVZtEsF9rkyRJWu9tNKqOk5wCPB/YNsn1DGZvngCcnuRI4FrgsLb5WcBLgKXAPcARAFW1PMnxwAVtu+OqauUJCpIkSeulkQW1qnr1OB/tu4ptCzhqnH4WAAvWYWmSJEnTgk8mkCRJ6imDmiRJUk8Z1CRJknrKoCZJktRTBjVJkqSeMqhJkiT1lEFNkiSppwxqkiRJPWVQkyRJ6imDmiRJUk8Z1CRJknrKoCZJktRTBjVJkqSeMqhJkiT1lEFNkiSppwxqkiRJPWVQkyRJ6imDmiRJUk8Z1CRJknrKoCZJktRTBjVJkqSeMqhJkiT1lEFNkiSppwxqkiRJPWVQkyRJ6imDmiRJUk8Z1CRJknrKoCZJktRTBjVJkqSeMqhJkiT1lEFNkiSpp6ZNUEuyf5IrkyxNcsxU1yNJkjRq0yKoJdkQ+BRwALAb8Ooku01tVZIkSaM1LYIasBewtKqurqpfA6cCh0xxTZIkSSM1XYLajsB1Q+vXtzZJkqT1VqpqqmtYrSSvAPavqje29dcBe1fVm4e2mQ/Mb6tPBa6c9EInz7bAL6a6CK01f7/py99uevP3m97W59/vSVW13ao+2GiyK1lLy4CdhtZnt7aHVNVJwEmTWdRUSbKkquZOdR1aO/5+05e/3fTm7ze9zdTfb7qc+rwA2DXJLkkeAxwOLJrimiRJkkZqWoyoVdX9Sd4MfAvYEFhQVZdNcVmSJEkjNS2CGkBVnQWcNdV19MSMOMW7HvP3m7787aY3f7/pbUb+ftNiMoEkSdJMNF2uUZMkSZpxDGrTSJIFSW5O8pOprkVrJslOSc5JcnmSy5IcPdU1qbskj0tyfpIft9/v/VNdk9ZMkg2T/CjJ16e6Fq2ZJNckuTTJxUmWTHU9k81Tn9NIkucBdwGfq6rfm+p61F2SHYAdquqiJJsDFwKHVtXlU1yaOkgSYNOquivJxsD3gKOr6rwpLk0dJXkbMBfYoqoOmup61F2Sa4C5VbW+3kNtQo6oTSNV9V1g+VTXoTVXVTdU1UVt+U7gCny6xrRRA3e11Y3by//LnSaSzAYOBP5xqmuR1pRBTZpkSeYAewA/nNpKtCbaqbOLgZuBxVXl7zd9fBx4B/DgVBeitVLAvyW5sD2FaEYxqEmTKMlmwJeAt1bVHVNdj7qrqgeqancGT0bZK4mXH0wDSQ4Cbq6qC6e6Fq2151bVnsABwFHtMqAZw6AmTZJ2bdOXgH+pqn+d6nq0dqrqNuAcYP+prkWdPAc4uF3ndCrwwiSfn9qStCaqall7vxn4MrDX1FY0uQxq0iRoF6OfDFxRVR+d6nq0ZpJsl2RWW94EeBHw06mtSl1U1TuranZVzWHw+MFvV9Vrp7gsdZRk0zYBiySbAvsBM+rOBwa1aSTJKcAPgKcmuT7JkVNdkzp7DvA6Bv83f3F7vWSqi1JnOwDnJLmEwbOHF1eVt3mQRm974HtJfgycD5xZVd+c4pomlbfnkCRJ6ilH1CRJknrKoCZJktRTBjVJkqSeMqhJkiT1lEFNkiSppwxqkmaUJA+026P8JMnXxu6PNsH2uw/fSiXJwUmOGX2lkuTtOSTNMEnuqqrN2vJC4GdV9cEJtn8DMLeq3jxJJUrSQzaa6gIkaQr9AHgGQJK9gE8AjwN+BRwB/Bw4DtgkyXOBDwGb0IJbks8CdwBzgScA76iqM5JsAHwSeCFwHfAbYEFVnTGJ303SesBTn5JmpCQbAvsCi1rTT4Hfr6o9gPcCf1VVv27Lp1XV7lV12iq62gF4LnAQcEJrexkwB9iNwRMpnj2q7yFp/eaImqSZZpMkFwM7AlcAi1v7lsDCJLsCBWzcsb+vVNWDwOVJtm9tzwW+2NpvTHLOuitf0kziiJqkmeZXVbU78CQgwFGt/XjgnKr6PeClDE6BdnHf0HLWWZWShEFN0gxVVfcAfw68PclGDEbUlrWP3zC06Z3A5mvY/f8FXp5kgzbK9vxHV62kmcqgJmnGqqofAZcArwb+GvhQkh+x4mUh5wC7tVt6vKpj118CrgcuBz4PXATcvs4KlzRjeHsOSRqBJJtV1V1JtgHOB55TVTdOdV2SphcnE0jSaHy93Uz3McDxhjRJa8MRNUmSpJ7yGjVJkqSeMqhJkiT1lEFNkiSppwxqkiRJPWVQkyRJ6imDmiRJUk/9/xgKICffpBT7AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  21872\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Thriller . Recommendations based on top average ratings.\n",
            "                                           rating\n",
            "movie title                                      \n",
            "Close Shave, A (1995)                    4.491071\n",
            "Rear Window (1954)                       4.387560\n",
            "Usual Suspects, The (1995)               4.385768\n",
            "Third Man, The (1949)                    4.333333\n",
            "Some Folks Call It a Sling Blade (1993)  4.292683\n",
            "Silence of the Lambs, The (1991)         4.289744\n",
            "North by Northwest (1959)                4.284916\n",
            "Manchurian Candidate, The (1962)         4.259542\n",
            "Vertigo (1958)                           4.251397\n",
            "Innocents, The (1961)                    4.250000\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Thriller genre. Recommendations based on Popularity\n",
            "                        movie title  Number of Users watched\n",
            "0                      Fargo (1996)                      508\n",
            "1                     Scream (1996)                      478\n",
            "2              Air Force One (1997)                      431\n",
            "3  Silence of the Lambs, The (1991)                      390\n",
            "4                  Rock, The (1996)                      378\n",
            "5              Fugitive, The (1993)                      336\n",
            "6                 Saint, The (1997)                      316\n",
            "7            Terminator, The (1984)                      301\n",
            "8          L.A. Confidential (1997)                      297\n",
            "9          Conspiracy Theory (1997)                      295\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  3.5  with atleast  250  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                          movie title    rating  Number of Users watched\n",
            "2          Usual Suspects, The (1995)  4.385768                      267\n",
            "5    Silence of the Lambs, The (1991)  4.289744                      390\n",
            "11           L.A. Confidential (1997)  4.161616                      297\n",
            "12                       Fargo (1996)  4.155512                      508\n",
            "20               Fugitive, The (1993)  4.044643                      336\n",
            "21                       Alien (1979)  4.034364                      291\n",
            "24  Terminator 2: Judgment Day (1991)  4.006780                      295\n",
            "34       2001: A Space Odyssey (1968)  3.969112                      259\n",
            "36                      Aliens (1986)  3.947183                      284\n",
            "37             Terminator, The (1984)  3.933555                      301\n",
            "39                   Apollo 13 (1995)  3.931159                      276\n",
            "54                   Rock, The (1996)  3.693122                      378\n",
            "58                      Ransom (1996)  3.644195                      267\n",
            "59               Air Force One (1997)  3.631090                      431\n",
            "65                   Game, The (1997)  3.593625                      251\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  War  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  9398\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: War . Recommendations based on top average ratings.\n",
            "                                                      rating\n",
            "movie title                                                 \n",
            "Schindler's List (1993)                             4.466443\n",
            "Casablanca (1942)                                   4.456790\n",
            "Star Wars (1977)                                    4.358491\n",
            "Dr. Strangelove or: How I Learned to Stop Worry...  4.252577\n",
            "Lawrence of Arabia (1962)                           4.231214\n",
            "Paths of Glory (1957)                               4.212121\n",
            "Empire Strikes Back, The (1980)                     4.204360\n",
            "Boot, Das (1981)                                    4.203980\n",
            "African Queen, The (1951)                           4.184211\n",
            "Bridge on the River Kwai, The (1957)                4.175758\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in War genre. Recommendations based on Popularity\n",
            "                       movie title  Number of Users watched\n",
            "0                 Star Wars (1977)                      583\n",
            "1        Return of the Jedi (1983)                      507\n",
            "2      English Patient, The (1996)                      481\n",
            "3    Independence Day (ID4) (1996)                      429\n",
            "4  Empire Strikes Back, The (1980)                      367\n",
            "5              Forrest Gump (1994)                      321\n",
            "6          Schindler's List (1993)                      298\n",
            "7                Braveheart (1995)                      297\n",
            "8                    Aliens (1986)                      284\n",
            "9                Casablanca (1942)                      243\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  3.5  with atleast  200  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                        movie title    rating  Number of Users watched\n",
            "0           Schindler's List (1993)  4.466443                      298\n",
            "1                 Casablanca (1942)  4.456790                      243\n",
            "2                  Star Wars (1977)  4.358491                      583\n",
            "6   Empire Strikes Back, The (1980)  4.204360                      367\n",
            "7                  Boot, Das (1981)  4.203980                      201\n",
            "10                Braveheart (1995)  4.151515                      297\n",
            "16            Apocalypse Now (1979)  4.045249                      221\n",
            "17        Return of the Jedi (1983)  4.007890                      507\n",
            "21                    Aliens (1986)  3.947183                      284\n",
            "22                   M*A*S*H (1970)  3.912621                      206\n",
            "24              Forrest Gump (1994)  3.853583                      321\n",
            "32      English Patient, The (1996)  3.656965                      481\n",
            "36        Courage Under Fire (1996)  3.610860                      221\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n",
            "****************************     ******************************     ******************************\n",
            "****************************     ****** GENRE:  Western  ******     ******************************\n",
            "    \n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  1854\n",
            "  \n",
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Western . Recommendations based on top average ratings.\n",
            "                                             rating\n",
            "movie title                                        \n",
            "High Noon (1952)                           4.102273\n",
            "Wild Bunch, The (1969)                     4.023256\n",
            "Butch Cassidy and the Sundance Kid (1969)  3.949074\n",
            "Magnificent Seven, The (1954)              3.942149\n",
            "Once Upon a Time in the West (1969)        3.868421\n",
            "Unforgiven (1992)                          3.868132\n",
            "Good, The Bad and The Ugly, The (1966)     3.861314\n",
            "Dead Man (1995)                            3.823529\n",
            "Dances with Wolves (1990)                  3.792969\n",
            "Tombstone (1993)                           3.666667\n",
            "****************************     ******************************     ******************************\n",
            "These are the most popular movies which can be recommended to a new user in Western genre. Recommendations based on Popularity\n",
            "                                 movie title  Number of Users watched\n",
            "0                  Dances with Wolves (1990)                      256\n",
            "1  Butch Cassidy and the Sundance Kid (1969)                      216\n",
            "2                          Unforgiven (1992)                      182\n",
            "3     Good, The Bad and The Ugly, The (1966)                      137\n",
            "4                            Maverick (1994)                      128\n",
            "5              Magnificent Seven, The (1954)                      121\n",
            "6                           Tombstone (1993)                      108\n",
            "7                          Young Guns (1988)                      101\n",
            "8                           High Noon (1952)                       88\n",
            "9                 Legends of the Fall (1994)                       81\n",
            "****************************     ******************************     ******************************\n",
            "These movies are the best to suggest to a new user within their requested genre as they are popular and well rated by the users who already watched them.\n",
            "These have rating more than  2.0  with atleast  50  viewers.\n",
            "**Recommendations based popularity and rating. These are top rated popular movies**\n",
            "                                  movie title  ...  Number of Users watched\n",
            "0                            High Noon (1952)  ...                       88\n",
            "2   Butch Cassidy and the Sundance Kid (1969)  ...                      216\n",
            "3               Magnificent Seven, The (1954)  ...                      121\n",
            "5                           Unforgiven (1992)  ...                      182\n",
            "6      Good, The Bad and The Ugly, The (1966)  ...                      137\n",
            "8                   Dances with Wolves (1990)  ...                      256\n",
            "9                            Tombstone (1993)  ...                      108\n",
            "10                            Maverick (1994)  ...                      128\n",
            "11                 Legends of the Fall (1994)  ...                       81\n",
            "13                          Young Guns (1988)  ...                      101\n",
            "21                   Last Man Standing (1996)  ...                       53\n",
            "\n",
            "[11 rows x 3 columns]\n",
            "****************************     ******************************     ******************************\n",
            "                             \n",
            "                             \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xMcFJgHlXGuR"
      },
      "source": [
        "We can see rating frequency plot, movie recommendation based on only high ratings, only popularity and high rated popular movie for each movie genre separately."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aneLfqrtXFk9"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IhY_79CI31QH"
      },
      "source": [
        "# Rough Work"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5lmhc7hi6Mvb",
        "outputId": "49870b24-c0ca-420f-ad7e-355e51694032",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "x = 'Western'\n",
        "genre_based_movies = items_dataset[['movie id','movie title',x]]\n",
        "genre_based_movies = genre_based_movies[genre_based_movies[x] == 1]\n",
        "merged_genre_movies = pd.merge(dataset, genre_based_movies, how='inner', on='movie id')\n",
        "merged_genre_movies.head()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>user id</th>\n",
              "      <th>movie id</th>\n",
              "      <th>rating</th>\n",
              "      <th>timestamp</th>\n",
              "      <th>movie title</th>\n",
              "      <th>Western</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>244</td>\n",
              "      <td>51</td>\n",
              "      <td>2</td>\n",
              "      <td>880606923</td>\n",
              "      <td>Legends of the Fall (1994)</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>85</td>\n",
              "      <td>51</td>\n",
              "      <td>2</td>\n",
              "      <td>879454782</td>\n",
              "      <td>Legends of the Fall (1994)</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>201</td>\n",
              "      <td>51</td>\n",
              "      <td>2</td>\n",
              "      <td>884140751</td>\n",
              "      <td>Legends of the Fall (1994)</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>198</td>\n",
              "      <td>51</td>\n",
              "      <td>3</td>\n",
              "      <td>884208455</td>\n",
              "      <td>Legends of the Fall (1994)</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>330</td>\n",
              "      <td>51</td>\n",
              "      <td>5</td>\n",
              "      <td>876546753</td>\n",
              "      <td>Legends of the Fall (1994)</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   user id  movie id  rating  timestamp                 movie title  Western\n",
              "0      244        51       2  880606923  Legends of the Fall (1994)        1\n",
              "1       85        51       2  879454782  Legends of the Fall (1994)        1\n",
              "2      201        51       2  884140751  Legends of the Fall (1994)        1\n",
              "3      198        51       3  884208455  Legends of the Fall (1994)        1\n",
              "4      330        51       5  876546753  Legends of the Fall (1994)        1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QTpavk0cMAzF",
        "outputId": "3c48eaac-f29a-4cea-bc4b-42a6c44529ce",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "len(merged_genre_movies)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1854"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aOFHbwc2KqQ7",
        "outputId": "dc9e169b-ad63-4809-c808-aa601a216c3a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        }
      },
      "source": [
        "star_based_visualization(merged_genre_movies)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Total number of users watched this Genre:  1854\n",
            "  \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w_M5bmyVDuM1",
        "outputId": "4a3a32a8-18e2-40d6-ef89-a7901e6c64bf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 427
        }
      },
      "source": [
        "high_rated_movies = merged_genre_movies.groupby(['movie title']).agg({\"rating\":\"mean\"})['rating'].sort_values(ascending=False)\n",
        "high_rated_movies = high_rated_movies.to_frame()\n",
        "print(\"These are the top movies that can be naviely suggested to the new users for the requested movie genre:\", x, \". Recommendations based on top average ratings.\")\n",
        "high_rated_movies.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "These are the top movies that can be naviely suggested to the new users for the requested movie genre: Western . Recommendations based on top average ratings.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>movie title</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>High Noon (1952)</th>\n",
              "      <td>4.102273</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Wild Bunch, The (1969)</th>\n",
              "      <td>4.023256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Butch Cassidy and the Sundance Kid (1969)</th>\n",
              "      <td>3.949074</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Magnificent Seven, The (1954)</th>\n",
              "      <td>3.942149</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Once Upon a Time in the West (1969)</th>\n",
              "      <td>3.868421</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Unforgiven (1992)</th>\n",
              "      <td>3.868132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Good, The Bad and The Ugly, The (1966)</th>\n",
              "      <td>3.861314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dead Man (1995)</th>\n",
              "      <td>3.823529</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dances with Wolves (1990)</th>\n",
              "      <td>3.792969</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tombstone (1993)</th>\n",
              "      <td>3.666667</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                             rating\n",
              "movie title                                        \n",
              "High Noon (1952)                           4.102273\n",
              "Wild Bunch, The (1969)                     4.023256\n",
              "Butch Cassidy and the Sundance Kid (1969)  3.949074\n",
              "Magnificent Seven, The (1954)              3.942149\n",
              "Once Upon a Time in the West (1969)        3.868421\n",
              "Unforgiven (1992)                          3.868132\n",
              "Good, The Bad and The Ugly, The (1966)     3.861314\n",
              "Dead Man (1995)                            3.823529\n",
              "Dances with Wolves (1990)                  3.792969\n",
              "Tombstone (1993)                           3.666667"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1r8n9xS4HQpj"
      },
      "source": [
        "popular_movies_ingenre = merged_genre_movies.groupby(['movie title']).agg({\"rating\":\"count\"})['rating'].sort_values(ascending=False)\n",
        "popular_movies_ingenre = popular_movies_ingenre.to_frame()\n",
        "popular_movies_ingenre.reset_index(level=0, inplace=True)\n",
        "popular_movies_ingenre.columns = ['movie title', 'Number of Users watched']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OqoyOQ3YPjwi",
        "outputId": "5f402fa2-f5e3-49f2-891b-4b54f5bab5ad",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        }
      },
      "source": [
        "# popular_movies[popular_movies['Number of Users watched'] >= 400]\n",
        "print(\"These are the most popular movies which can be recommended to a new user in\",x,\"genre. Recommendations based on Popularity\")\n",
        "popular_movies_ingenre.sort_values('Number of Users watched', ascending=False).head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "These are the most popular movies which can be recommended to a new user in Western genre. Recommendations based on Popularity\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie title</th>\n",
              "      <th>Number of Users watched</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Dances with Wolves (1990)</td>\n",
              "      <td>256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Butch Cassidy and the Sundance Kid (1969)</td>\n",
              "      <td>216</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Unforgiven (1992)</td>\n",
              "      <td>182</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Good, The Bad and The Ugly, The (1966)</td>\n",
              "      <td>137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Maverick (1994)</td>\n",
              "      <td>128</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Magnificent Seven, The (1954)</td>\n",
              "      <td>121</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Tombstone (1993)</td>\n",
              "      <td>108</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Young Guns (1988)</td>\n",
              "      <td>101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>High Noon (1952)</td>\n",
              "      <td>88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Legends of the Fall (1994)</td>\n",
              "      <td>81</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                 movie title  Number of Users watched\n",
              "0                  Dances with Wolves (1990)                      256\n",
              "1  Butch Cassidy and the Sundance Kid (1969)                      216\n",
              "2                          Unforgiven (1992)                      182\n",
              "3     Good, The Bad and The Ugly, The (1966)                      137\n",
              "4                            Maverick (1994)                      128\n",
              "5              Magnificent Seven, The (1954)                      121\n",
              "6                           Tombstone (1993)                      108\n",
              "7                          Young Guns (1988)                      101\n",
              "8                           High Noon (1952)                       88\n",
              "9                 Legends of the Fall (1994)                       81"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 112
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pef6XJRkAuH1",
        "outputId": "f44d1bbb-7047-42f9-d432-538cf2149553",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        }
      },
      "source": [
        "highly_rated_popular_movies = pd.merge(high_rated_movies, popular_movies_ingenre, how = 'inner', on='movie title')\n",
        "highly_rated_popular_movies.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie title</th>\n",
              "      <th>rating</th>\n",
              "      <th>Number of Users watched</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>High Noon (1952)</td>\n",
              "      <td>4.102273</td>\n",
              "      <td>88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Wild Bunch, The (1969)</td>\n",
              "      <td>4.023256</td>\n",
              "      <td>43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Butch Cassidy and the Sundance Kid (1969)</td>\n",
              "      <td>3.949074</td>\n",
              "      <td>216</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Magnificent Seven, The (1954)</td>\n",
              "      <td>3.942149</td>\n",
              "      <td>121</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Once Upon a Time in the West (1969)</td>\n",
              "      <td>3.868421</td>\n",
              "      <td>38</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Unforgiven (1992)</td>\n",
              "      <td>3.868132</td>\n",
              "      <td>182</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Good, The Bad and The Ugly, The (1966)</td>\n",
              "      <td>3.861314</td>\n",
              "      <td>137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Dead Man (1995)</td>\n",
              "      <td>3.823529</td>\n",
              "      <td>34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Dances with Wolves (1990)</td>\n",
              "      <td>3.792969</td>\n",
              "      <td>256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Tombstone (1993)</td>\n",
              "      <td>3.666667</td>\n",
              "      <td>108</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                 movie title    rating  Number of Users watched\n",
              "0                           High Noon (1952)  4.102273                       88\n",
              "1                     Wild Bunch, The (1969)  4.023256                       43\n",
              "2  Butch Cassidy and the Sundance Kid (1969)  3.949074                      216\n",
              "3              Magnificent Seven, The (1954)  3.942149                      121\n",
              "4        Once Upon a Time in the West (1969)  3.868421                       38\n",
              "5                          Unforgiven (1992)  3.868132                      182\n",
              "6     Good, The Bad and The Ugly, The (1966)  3.861314                      137\n",
              "7                            Dead Man (1995)  3.823529                       34\n",
              "8                  Dances with Wolves (1990)  3.792969                      256\n",
              "9                           Tombstone (1993)  3.666667                      108"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 113
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EL33xBMOAuNy",
        "outputId": "7be38ef4-1d4c-46f0-8f02-118ccb9e63c6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        }
      },
      "source": [
        "viewer_limit = 300\n",
        "ratings_limit = 4.0\n",
        "count = 0\n",
        "check = 0\n",
        "while viewer_limit > 0 and ratings_limit > 0:\n",
        "  s = highly_rated_popular_movies[(highly_rated_popular_movies['Number of Users watched']>viewer_limit) & (highly_rated_popular_movies['rating']>=ratings_limit)]\n",
        "  if len(s) < 11:\n",
        "    if check == 0:\n",
        "      viewer_limit -= 50\n",
        "      check = 1\n",
        "    else:\n",
        "      ratings_limit -= 0.5\n",
        "      check = 0\n",
        "  else:\n",
        "    break\n",
        "s"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie title</th>\n",
              "      <th>rating</th>\n",
              "      <th>Number of Users watched</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>High Noon (1952)</td>\n",
              "      <td>4.102273</td>\n",
              "      <td>88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Butch Cassidy and the Sundance Kid (1969)</td>\n",
              "      <td>3.949074</td>\n",
              "      <td>216</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Magnificent Seven, The (1954)</td>\n",
              "      <td>3.942149</td>\n",
              "      <td>121</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Unforgiven (1992)</td>\n",
              "      <td>3.868132</td>\n",
              "      <td>182</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Good, The Bad and The Ugly, The (1966)</td>\n",
              "      <td>3.861314</td>\n",
              "      <td>137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Dances with Wolves (1990)</td>\n",
              "      <td>3.792969</td>\n",
              "      <td>256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Tombstone (1993)</td>\n",
              "      <td>3.666667</td>\n",
              "      <td>108</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Maverick (1994)</td>\n",
              "      <td>3.468750</td>\n",
              "      <td>128</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Legends of the Fall (1994)</td>\n",
              "      <td>3.456790</td>\n",
              "      <td>81</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Young Guns (1988)</td>\n",
              "      <td>3.207921</td>\n",
              "      <td>101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Last Man Standing (1996)</td>\n",
              "      <td>2.660377</td>\n",
              "      <td>53</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                  movie title  ...  Number of Users watched\n",
              "0                            High Noon (1952)  ...                       88\n",
              "2   Butch Cassidy and the Sundance Kid (1969)  ...                      216\n",
              "3               Magnificent Seven, The (1954)  ...                      121\n",
              "5                           Unforgiven (1992)  ...                      182\n",
              "6      Good, The Bad and The Ugly, The (1966)  ...                      137\n",
              "8                   Dances with Wolves (1990)  ...                      256\n",
              "9                            Tombstone (1993)  ...                      108\n",
              "10                            Maverick (1994)  ...                      128\n",
              "11                 Legends of the Fall (1994)  ...                       81\n",
              "13                          Young Guns (1988)  ...                      101\n",
              "21                   Last Man Standing (1996)  ...                       53\n",
              "\n",
              "[11 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 114
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LkwH-StRfPsT",
        "outputId": "1013fd50-5c0b-4c87-c431-f473172ef8a2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "a, r = 20,5.0\n",
        "# highly_rated_popular_movies[(highly_rated_popular_movies['Number of Users watched']<a) & (highly_rated_popular_movies['rating']<r)]\n",
        "len(popular_movies_ingenre)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "50"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 106
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3lVKbR0KCNTA",
        "outputId": "b3b3d6fe-c1d3-45a8-d9f3-e2579a2ce91e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85
        }
      },
      "source": [
        "df = pd.DataFrame([[1, 2, 3], [4, 5, 1], [4, 5, 6]], columns = [\"a\", \"b\", \"c\"])\n",
        "print(df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "   a  b  c\n",
            "0  1  2  3\n",
            "1  4  5  1\n",
            "2  4  5  6\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LaNy-AFXCNWy",
        "outputId": "41a7faa0-5236-407e-c90d-eddccaa95178",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85
        }
      },
      "source": [
        "df = df.sort_values([\"b\", \"c\"], ascending = (False, False))\n",
        "print(df)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "   a  b  c\n",
            "2  4  5  6\n",
            "1  4  5  1\n",
            "0  1  2  3\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_rE2aZFmEYxd",
        "outputId": "5a639e59-ea20-4139-e293-2b9b8b2a88d8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 758
        }
      },
      "source": [
        "items_dataset"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie id</th>\n",
              "      <th>movie title</th>\n",
              "      <th>release date</th>\n",
              "      <th>video release date</th>\n",
              "      <th>IMDb URL</th>\n",
              "      <th>unknown</th>\n",
              "      <th>Action</th>\n",
              "      <th>Adventure</th>\n",
              "      <th>Animation</th>\n",
              "      <th>Children</th>\n",
              "      <th>Comedy</th>\n",
              "      <th>Crime</th>\n",
              "      <th>Documentary</th>\n",
              "      <th>Drama</th>\n",
              "      <th>Fantasy</th>\n",
              "      <th>Film-Noir</th>\n",
              "      <th>Horror</th>\n",
              "      <th>Musical</th>\n",
              "      <th>Mystery</th>\n",
              "      <th>Romance</th>\n",
              "      <th>Sci-Fi</th>\n",
              "      <th>Thriller</th>\n",
              "      <th>War</th>\n",
              "      <th>Western</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Toy Story (1995)</td>\n",
              "      <td>01-Jan-1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Toy%20Story%2...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>GoldenEye (1995)</td>\n",
              "      <td>01-Jan-1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?GoldenEye%20(...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Four Rooms (1995)</td>\n",
              "      <td>01-Jan-1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Four%20Rooms%...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Get Shorty (1995)</td>\n",
              "      <td>01-Jan-1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Get%20Shorty%...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Copycat (1995)</td>\n",
              "      <td>01-Jan-1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Copycat%20(1995)</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1677</th>\n",
              "      <td>1678</td>\n",
              "      <td>Mat' i syn (1997)</td>\n",
              "      <td>06-Feb-1998</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Mat%27+i+syn+...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1678</th>\n",
              "      <td>1679</td>\n",
              "      <td>B. Monkey (1998)</td>\n",
              "      <td>06-Feb-1998</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?B%2E+Monkey+(...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1679</th>\n",
              "      <td>1680</td>\n",
              "      <td>Sliding Doors (1998)</td>\n",
              "      <td>01-Jan-1998</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/Title?Sliding+Doors+(1998)</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1680</th>\n",
              "      <td>1681</td>\n",
              "      <td>You So Crazy (1994)</td>\n",
              "      <td>01-Jan-1994</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?You%20So%20Cr...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1681</th>\n",
              "      <td>1682</td>\n",
              "      <td>Scream of Stone (Schrei aus Stein) (1991)</td>\n",
              "      <td>08-Mar-1996</td>\n",
              "      <td>NaN</td>\n",
              "      <td>http://us.imdb.com/M/title-exact?Schrei%20aus%...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1682 rows × 24 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      movie id                                movie title  ... War  Western\n",
              "0            1                           Toy Story (1995)  ...   0        0\n",
              "1            2                           GoldenEye (1995)  ...   0        0\n",
              "2            3                          Four Rooms (1995)  ...   0        0\n",
              "3            4                          Get Shorty (1995)  ...   0        0\n",
              "4            5                             Copycat (1995)  ...   0        0\n",
              "...        ...                                        ...  ...  ..      ...\n",
              "1677      1678                          Mat' i syn (1997)  ...   0        0\n",
              "1678      1679                           B. Monkey (1998)  ...   0        0\n",
              "1679      1680                       Sliding Doors (1998)  ...   0        0\n",
              "1680      1681                        You So Crazy (1994)  ...   0        0\n",
              "1681      1682  Scream of Stone (Schrei aus Stein) (1991)  ...   0        0\n",
              "\n",
              "[1682 rows x 24 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 185
        }
      ]
    }
  ]
}
